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Water Quality Inventory and Monitoring-
Gates of the Arctic National Park
and Preserve, 1992-1995
Jacqueline D. LaPerriere
Alaska Cooperative Fish and Wildlife Research Unit
Biological Resources Division, U.S. Geological Survey
Final Report
to the
National Park Service
Unit Cooperative Agreement No. 14-48-009-1582
Research Work Order No. 4
1999
FORT
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Water Quality Inventory and Monitoring-
Gates of the Arctic National Park
and Preserve, 1992-1995
Jacqueline D. LaPerriere
Alaska Cooperative Fish and Wildlife Research Unit
Biological Resources Division, U.S. Geological Survey
Final Report
to the
National Park Service
Unit Cooperative Agreement No. 1 4-48-009-1 582
Research Work Order No. 4
1999
Digitized by the Internet Archive
in 2012 with funding from
LYRASIS Members and Sloan Foundation
http://archive.org/details/waterqualityinve99lape
Contents
Executive Summary 1
Introduction 3
Study Site 3
Methods 4
General Limnology, Nutrients, and Plankton 4
Geomorphology and Landscape Characteristics 7
Nutrient Stimulation Experiments 7
Periphyton 7
Streams .8
Quality Assurance/Quality Control 8
Results and Discussion 9
Landscape and Geomorphology 9
Profiles 9
Major Ions 12
Trace Metals 13
Nutrients and Phytoplankton 14
Light Conditions 16
Periphyton 17
Zooplankton 18
Lake Productivity 18
John River 20
Future Research 21
Acknowledgments 22
References 23
Glossary 28
Tables 31
Table 1 . The study lakes, Gates of the Arctic National Park and Preserve 31
Table 2. Geomorphic and landscape characteristics of lakes of GAAR 32
Table 3. Major ion balances, lakes of GAAR 33
Table 4. Trace metal characteristics of Gates of the Arctic samples, as total
recoverable metals 35
Table 5. Mean nutrients and phytoplankton biomass in lakes of GAAR 36
Table 6. Multi-year average nutrients and phytoplankton biomass in
lakes of GAAR 37
Contents, continued
Table 7. Results of nutrient stimulation bioassay experiments in lakes of
GAAR, expressed as ratio of final to initial total chlorophyll 38
Table 8. Discrete total chlorophyll values for specific depths, lakes of GAAR 39
Table 9. Light levels at depths of total chlorophyll peaks, lakes of GAAR .40
Table 1 0. Light conditions, lakes of GAAR 41
Table 1 1 . Composite light characteristics, lakes of GAAR 42
Table 12. Average concentrations of zooplankton as dry weight and as
organic material for lakes of GAAR 43
Table 1 3. Counts of zooplankton, 1 993 samples, lakes of GAAR 44
Table 1 4. Counts of copepods, 1 993 zooplankton samples, lakes of GAAR 45
Table 1 5. Productivity indicator ranking — high to low — of lakes of GAAR 46
Table 1 6. Stream conditions, John River and tributaries at Anaktuvuk Pass 47
Table 1 7. Ion balances, John River and tributaries at Anaktuvuk Pass 48
Table 1 8. Trace metal characteristics of the upper John River samples,
September 1 993 49
Table 1 9. Bacterial analysis, John River and tributaries, late summer
1 993 and 1 994 50
Table 20. Total petroleum hydrocarbons, John River and tributaries, 1993
and 1994 51
Figures 52
Gates of the Arctic National Park and Preserve with study lakes
and streams 52
Figure 1 .
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Figure 9.
Figure 10.
Figure 1 1 .
Figure 12.
Figure 13.
Water quality pro
Water quality pro
Water quality pro
Water quality pro
Water quality pro
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iles, Agiak Lake 53
iles, Amiloyak Lake 54
iles, Chandler Lake 55
i les, Itki 1 1 i k Lake 5 6
iles, Kipmik Lake 57
iles, Matcharak Lake 58
iles, Narvak Lake 59
iles, Nutuvukti Lake 60
iles, Selby Lake 61
iles, Summit Lake 62
iles, Takahula Lake 63
Temperature profiles, Walker Lake, 1988 64
Contents, continued
Figure 14. Water quality profiles, Walker Lake 65
Figure 15. Water quality profiles, Minakokosa, Pingo, Kurupa, and
Tulilik lakes 66
Figure 1 6. Relation between magnesium and calcium in lakes of GAAR 67
Figure 1 7. Fish density and the morphoedaphic index of four lakes, GAAR 68
Appendixes 69
Appendix A. Bathymetric maps of study lakes that are mapped, GAAR 69
Appendix B. Trace and major metals (mg/L) of lakes of GAAR — 1 992,
1993, and 1995 83
Appendix C. Nutrients and total chlorophyll concentrations of plankton
of lakes of GAAR— 1 992, 1 993, and 1 995 88
Appendix D. Light characteristics of lakes of GAAR— 1 992, 1 993, and 1 995 90
Appendix E. Trace and major ions of the John River, Big Contact Creek,
and Little Contact Creek near Anaktuvuk Pass and Reed River
Hot Springs, Alaska, August 1993 93
Appendix F. Monitoring Plan 96
in
Executive Summary
Gates of the Arctic National Park and Preserve (GAAR), the second largest national park of
the U.S. at 3.4 million hectares, is estimated to contain tens of thousands of lakes. Sixteen
lakes in GAAR were studied limnologically in the early summers of 1992, 1993, and 1995.
Additionally, the John River near Anaktuvuk Pass and two of its tributaries above the
village were studied in summers 1993 and 1994.
Lakes were found to be variable in mixing and chemical types. Lakes to the north
in GAAR and shallow lakes to the south do not stratify; therefore, they are discontinuous
cold polymictic lakes. Deep lakes to the south in GAAR apparently summer-stratify. These
deep, southern lakes may miss some spring overturns as they sometimes had hypolimnetic
waters colder than 4°C, the temperature of maximum density, especially in 1 992. This
phenomenon may also be due to local degradation of permafrost caused by recent
climactic warming.
Most of the lakes studied are calcium carbonate lakes, but Pingo Lake, at the head
of the Noatak watershed, is a magnesium-calcium carbonate lake, and Chandler Lake,
near the headwaters of the Chandler River, is a calcium sulfate-bicarbonate lake. The high
sulfate in Chandler Lake may come from the presence of reduced sulfur rocks in the lake's
watershed, though this was not established. In 1995, when Chandler Lake was turbid from
recent snowmelt and ice-off, total recoverable copper was measured.
All 1 6 lakes would be classified as oligotrophic on the basis of the total chlorophyll
biomass estimates of the phytoplankton. Phosphorus and nitrogen concentrations
exceeded the published boundary of oligotrophic-mesotrophic classification in Matcharak
Lake. This lake also showed deoxygenation of its deep waters, which typically is due to the
degradation of organics. In this lake, however, deoxygenation may instead be due to
missed vernal overturns or to intrusion of deoxygenated water from melting permafrost.
Lake nutrient stimulation bioassay experiments all showed that nitrogen and
phosphorus when added together were most stimulating to plankton algal growth.
Additionally, southern lakes that were tested showed phosphorus limitation as did
Chandler Lake, a northern lake, which is dominated by sulfate among the anions. The
other northern lakes that were tested showed nitrogen limitation.
Plankton chlorophyll maxima at depth were common in these lakes at light levels
between 1 and 4% of surface light. These plankton may be low-light adapted algae that
bloom under the ice in spring and seek a lower position with reduced light after ice-off
during the summer.
There was no general relation found among all these lakes between nutrients and
plankton algal biomass, nor among plankton biomass and Secchi transparency. This may
be due to the color and turbidity of many of these lakes, which are caused by dissolved
organic and inorganic materials rather than by plankton.
The seasonal growth of benthic algae in the ice-scour zone (< 2 m) of Selby Lake
was sampled in early July. The whole-lake average standing crop of benthic algae was
estimated as approximately equal to the whole-lake standing crop of phytoplankton. Local
density of benthic algae was greater near inlets than distant from inlets. Greater density
was associated with colder inlets and with those higher in total nitrogen.
All of the lakes sampled in 1993 for counts of zooplankton had cladocerans (water
fleas). On that basis, these lakes would be classified among arctic lakes of the highest
trophic status, but still oligotrophic.
A model relating fish productivity to the saltiness of lakes and their mean depths
developed from four lakes where fish standing crop has been measured ranked two lakes
with higher measured standing crops of fish and saltiness per mean depth as more
productive than the two lakes with lower standing crops and lower saltiness per mean
depth. The model then predicts Pingo, Itkillik, Tulilik, and Matcharak lakes higher in
potential fish yield and Kipmik, Walker, Minakokosa, and Narvak lakes lower.
Of the streams in Anaktuvuk Pass that were sampled, Little Contact Creek had the
highest conductivity (and associated major ions), Big Contact Creek had the lowest
conductivity, and the John River had an intermediate conductivity. Coliform bacteria and
total petroleum hydrocarbons were not found to be measurable in these streams, but
sampling was very limited over two days in late summer in each of two years.
Introduction
The most recent reviews of limnological studies conducted in the Arctic are by Hobbie
(1 973 and 1 983). Few of the thousands of waterbodies in the western North American
Arctic have been studied. Hobbie's reviews cover the findings of the thorough studies of
Peters and Schrader lakes (Hobbie, 1962), of Char and Meretta lakes on Comwallis Island,
Canada (Rigler et al., 1 974; Schindler et al., 1 974a; Schindler et al., 1 974b; Welch and
Kalff, 1974), and of ponds near Barrow, Alaska (Hobbie, 1980). The long-term, more
recent studies of Toolik Lake, Alaska, in the northern foothills of the Brooks Range and just
outside Gates of the Arctic (GAAR) National Park and Preserve have recently been
summarized by O'Brien (1997). Berger (1977) provides a summary of the Canadian work
on the Mackenzie Valley Pipeline studies.
Other papers concerning less intensive studies of aquatic systems near Cape
Thompson, Alaska (Watson et al., 1 966), near the Beaufort Sea coast (Kalff, 1 968), on the
Coville River Delta, Alaska (Kinney et al., 1 972), and along the Noatak River (O'Brien et
al., 1975) were also considered in Hobbie's reviews. Hobbie (1997) has also recently
written an interesting history of limnological research in Alaska.
Streams of the north slope of the Brooks Range have been surveyed and classified
(Craig and McCart, 1975), and one river, the upper Kuparuk River, has been intensely
studied (Peterson et al., 1 985) and a synoptic study of the entire river has been conducted
(Hersheyetal., 1997).
The objectives of the current study were to (1 ) inventory and characterize the major
lakes of GAAR to determine their trophic status and evaluate whether phytoplankton are
limited by nitrogen or phosphorus; (2) develop a baseline inventory of water quality
characteristics important to aquatic life in major lakes; (3) identify and document the
magnitude and direction of changes in water quality of the John River at several sites in
GAAR to determine if runoff and leachate from the village of Anaktuvuk Pass alter
conditions in the river; and (4) develop a long-term monitoring plan for use by GAAR staff.
Study Site
Gates of the Arctic National Park and Preserve (GAAR) is the second largest national park
in the nation at 3.4 million hectares (8.4 million acres) or 34 thousand km2 (13 thousand
mi2) in area. The number of lakes within GAAR is unknown but is estimated to be in the
tens of thousands, calculated from proportion to the area of Alaska at 1 1 .5 million km2
(570,833 mi2), which contains approximately 3 million lakes (Bue, 1963). GAAR lies to the
west of the Trans-Alaska Oil Pipeline and its service road, the Dalton Highway. The
primary means of access is by small airplane.
Sixteen lakes (Figure 1) were synoptically sampled during this study in summers
1992, 1993, and 1995. Chandler, Kipmik, Matcharak, Takahula, and Walker lakes were
sampled all three years. Agiak, Amiloyak, Itkillik, Narvak, Nutuvukti, and Summit lakes
were sampled two of the three years. Kurupa, Minakokosa, Pingo, Selby, and Tulilik lakes
were sampled only once.
Nine of these lakes were bathymetrically surveyed by Reanier and Anderson
(undated), and four of them were surveyed in 1991 by National Park Service personnel
(Appendix A). Three of the lakes do not yet have bathymetric maps. Most of these lakes are
in glacially eroded troughs (Reanier and Anderson, undated) and therefore are deep
(Table 1).
A limited stream study was conducted in late summer 1993 and 1994 on the upper
John River and its tributaries, Big and Little Contact creeks (Figure 1), near the village of
Anaktuvuk Pass. These waters lie outside GAAR on native lands. The John River enters
GAAR below the sampling site and is mostly contained in GAAR.
Methods
General Limnology, Nutrients, and Plankton
Lakes were accessed by Gates of the Arctic National Park and Preserve (GAAR) or charter
airplanes on floats during mid-July 1 992 and 1 993 and about a week earlier in 1 995. We
landed and anchored at the deepest spot, providing that winds were low enough to allow
use of the airplane floats as a steady work platform. We selected a safer site out of the
wind effects, in the cases of winds causing large waves or whitecaps at the preselected
station.
Secchi disk transparency was measured using a standard 20-centimeter (cm)
weighted disk of alternating black-and-white quadrants. It was lowered on a calibrated,
unstretchable, braided wire-line until it was no longer visible and retrieved until it could
just be seen, and the depth was then read off the line at the surface. This was repeated
three times and the average value calculated.
In 1993 and 1995, the penetration of photosynthetically active radiation (PAR) was
measured at each lake both sampling periods using a Li-Cor® 185B quantum radiometer
photometer with an LI-193SA spherical quantum sensor that measures aquatic quantum
scalar (downward plus upward) irradiance. The spherical sensor was held in an
underwater lowering frame which was attached to the calibrated wire-line described
above. Data were taken at each meter of depth until values fell to approximately 1 % of the
irradiance measured immediately under the water surface. Percentage of irradiance was
plotted versus depth on semi-log graph paper, and the slope of the best straight line
connecting the points was calculated as the vertical attenuation coefficient of downward
irradiance, Kd. This coefficient is equivalent whether the sensor used is flat (cosine) or
essentially three-dimensional (spherical or scalar) (Kirk, 1994).
In 1 992, samples for water color and turbidity, major ions, and nutrients were
taken in triplicate with an opaque 2-liter (L) Van Dorn sampler at a depth of 2 meters (m)
and delivered into 1-L cubitainers and placed in an insulated cooler. Trace metal samples
were taken in the same way and delivered into new, acid pre-cleaned 250-milliliter (mL)
Nalgene bottles and stored in a cooler. Also in 1992, phytoplankton samples for biomass
estimates (as chlorophyll) were taken with the same sampler and handled the same way as
the color and turbidity samples, but triplicate phytoplankton samples were taken at depths
of 1 m, the Secchi depth, and twice the Secchi depth. In 1993 and 1995, samples were all
integrated through depth with a weighted 13-millimeter (mm) (i.d.) Tygon tube lowered to
twice the Secchi depth (Hanna and Peters, 1991).
Depth profiles of physical and chemical characteristics were taken using a YSI
Model 3800 multimeter fitted with depth, temperature, pH, conductivity, oxidation/
reduction potential, and dissolved oxygen probes. Calibration of the unit was conducted
every few days and whenever any sensor maintenance was required. Readings of dissolved
oxygen were corrected for the altitude of the lake with a built-in barometer. Conductivity
was automatically corrected to 25°C by the electronics of the meter. When the meter
flooded and failed in 1993, temperature and oxygen readings were made with a YSI Model
56 meter; Park personnel also used that meter in August and September 1 991 .
Vertical hauls with a zooplankton net (0.235 m x 1 m) of 20 mesh (0.001 cm) were
made in triplicate from the bottom of each lake at the sampling station. These samples
were emptied into 60-mL Nalgene bottles, and these were placed into a cooler.
Upon return to the local, temporary laboratory, apparent (unfiltered) color was read
at 455 nannometers (nm) on a HACH 2000 spectrophotometer, and turbidity was read on
a HACH Model 16800 Portalab turbidimeter (nephelometer) or a HACH Model 21 OOP
hand-held turbidimeter (1 995). All samples for planktonic chlorophyll analysis were
prepared by filtering 1-L samples through a Gelman GF/C glass-fiber filter. Filters were
made alkaline by adding 1 mL of saturated MgCC>3 to the last few mL of sample filtered,
and were stored frozen over desiccant until processed for chlorophyll at the laboratories of
the University of Alaska Fairbanks (UAF).
Alkalinity was titrated using the HACH procedure for the digital titrator (hand-held
buret) on 200-mL samples using the more dilute 0.1 600 N sulfuric acid cartridges. The
endpoint for total alkalinity (usually a pH of 5.1) was sensed with bromcresol green-methyl
red indicator. Since the initial pH was always below 8.3, we stopped adding
phenolphthalein at the beginning of the titration, because we found that it added
significant apparent alkalinity to these low-alkalinity waters by shifting the initial pH of the
water.
Chloride was titrated using HACH's digital titrator method on 100-mL samples
using their digital-titrator mercuric nitrate method in 1992 and 1993. Lower concentration
titrant cartridges (0.2256N Hg (NC>3)2) were used because of low levels of chloride in the
samples. Chloride was not measured in 1995 because all previous measurements were
below the detection limit (0.1 mg/L). Sulfate was analyzed using HACH's turbidimetric
method using (25-mL) Accuvac Ampules, which were read on the HACH 2000
spectrophotometer.
For phosphorus and nitrogen, triplicate samples were placed into acid-washed
screw-cap culture tubes at the field laboratory, and the nitrogen tubes were preserved with
20 microliters (uL) of 50% sulfuric acid. These samples were shipped to the limnology
laboratory of Dr. John R. Jones at the University of Missouri, Columbia, where they were
analyzed for total phosphorus and total nitrogen as labeled on each tube. Acidic persulfate
digestion was carried out in all the tubes, and the molybdate blue species of phosphorus
was read on phosphorus samples using a Milton Roy 1201 spectrophotometer. Nitrogen
was read for nitrogen samples on the nitrate formed during digestion by the
second-derivative spectroscopy method of Crumpton, Isenhart, and Mitchell (1992).
Chlorophyll filters were extracted in hot ethanol (Satory and Grobbelaar, 1984),
and samples were analyzed for total chlorophyll (not corrected for phaeopigments) on a
fluorometer (Knowlton, 1984). Zooplankton samples were preserved at the field laboratory
with 3 mL of buffered formalin and shipped to our laboratories at UAF. Zooplankton
samples were washed to remove the buffered formalin preservative and then analyzed for
dry weight and ash-free dry weight (organic content) using pre-ignited and tared glass-fiber
filters according to Standard Methods (APHA et al., 1 989).
Trace metal samples were refrigerated at the field laboratory and shipped to UAF,
where they were preserved with 0.3 mL of Ultrex -grade concentrated nitric acid and
shipped to Environmental Trace Substances Research Laboratory (TSRL) in Columbia,
Missouri, where they were acid digested for total recoverable metals and analyzed by
induced coupled plasma spectroscopy (ICP) scanning for 30 elements.
Data were normalized by log transformations if necessary, and data exploration
and statistics were conducted with JMP™ software (SAS Institute, 1994).
Geomorphology and Landscape Characteristics
Altitudes and latitudinal location of lakes were read on topographic maps. Lake surface
areas, volumes, and mean depths were measured by Dr. John R. Jones' Limnology
Laboratory at the University of Missouri on Reanier and Anderson's (undated) bathymetric
maps and by the author on bathymetric maps generated by GAAR personnel and drafted
by Betsy Sturm. Watershed areas were measured on U.S. Geological Survey (USGS)
topographic maps by Dr. David Swanson of the School of Agriculture and Land Resources
Management, UAF. Dr. Swanson also estimated landform, soil, and vegetation cover
characteristics from the 1 :60,000 color high-altitude infrared photo series, and geology of
the basins from USGS geologic maps (Brosge et al., 1 979; Chapman et al., 1 964; Ferrians,
1965; Grybecketal., 1977; Kelley, 1990; Patton and Miller, 1966).
Nutrient Stimulation Experiments
Lake planktonic algal stimulation bioassay experiments were conducted on Selby and
Narvak lakes in 1 993 (LaPerriere et al., 1 998), and on Agiak, Chandler, Itkillik, Kipmik,
Matcharak, and Summit lakes in 1 995. Similar experiments were conducted before this
project at Walker Lake in 1 988 Gones et al., 1 990) and at Itkillik Lake in 1 989 (LaPerriere
and Jones, 1991). Near-surface water was sampled and placed into 10-L cubitainers.
Triplicate containers were treated with nitrogen, adding 75 micrograms per liter (ug/L)
using ammonium nitrate, with phosphorus adding 5 ug/L using sodium orthophosphate,
with both nitrogen and phosphorus together at the above concentrations, and with no
chemical additions as controls.
The cubitainers were attached to an anchored, buoyed line at one-half of the
Secchi depth and allowed to incubate at ambient conditions for 4 or 5 days. When
retrieved, the cubitainers were returned to the field laboratory in dark containers, and
replicate subsamples were immediately filtered through GF-F glass fiber filters and treated
as all other chlorophyll samples.
Periphyton
Benthic algae was sampled intensively from random rocks in the ice-scour zone in Selby
Lake the second week of July 1993. Biomass was measured as chlorophyll (APHA et al.,
1989). The detailed methods are published in LaPerriere et al. (1998).
8
Streams
In the study in 1 993 and 1 994 of the John River and its two tributaries, Big and Little
Contact creeks, flow was measured by the velocity area technique (Gregory and Walling,
1973) using a Marsh-McBirney electric-field water velocity meter and a top-setting rod. In
1993, anion samples were taken in pre-cleaned polypropylene bottles and transported to
the field and UAF labs for analysis. Major ions were measured: alkalinity by the HACH
digital titrator method described above for lake work as soon as possible at the field lab.
Chloride and sulfate were measured by HACH methods as described above after return to
UAF. Trace metal samples were handled and analyzed in the same manner as the lake
samples as described above.
Laboratory-prepared bottles were used in both years to obtain coliform bacteria
and total petroleum hydrocarbon samples. These were returned within 24 hours to
Northern Testing Laboratories, where coliforms were measured by the Colilert method and
by fecal coliform membrane filtration. Total petroleum hydrocarbons were analyzed by
USEPA method 41 8.1.
On site, at the streams, a Corning Checkmate hand-held multimeter was used to
measure temperature, pH, conductivity, and occasionally dissolved oxygen. Color and
turbidity were measured by utilizing extra water from anion samples and using a HACH
2000 spectrophotometer to read color at 455 mm, and using a HACH Model 1 6800
turbidimeter to read turbidity.
Quality Assurance/Quality Control
Precision of the analytical methods was assured by measurements on replicate (usually
triplicate) samples. Accuracy of chemical measurements was assured by the method of
standard additions in which increasing concentrations of the appropriate primary standard
were added to three subsamples of a sample, and the analytical measurement made on
each. Results were plotted on square-matrix graph paper, and the true value of the
analyete in the sample was found graphically. This test was conducted on 5% of the
samples and whenever a new batch of chemicals was opened for use. Reagent blanks were
measured on reagent grade water and subtracted when necessary.
ICP samples were sent to the TSRL as triplicates from each waterbody in totally
randomized numbered bottles. The TSRL analyzed duplicate subsamples and blanks, as
well as spiking samples with standards and measuring the percentage recovery of the
spike. All the above tests showed TSRL results to be acceptably accurate and precise.
Results and Discussion
Landscape and Geomorphology
Because of the location of the Brooks Range and its foothills, southern lakes (~67°N) are at
lower altitude than northern lakes (~68°N) in Gates of the Arctic National Park and
Preserve (GAAR) (Figure 1, Table 2). As expected, larger lakes are associated with larger
watersheds (Table 2).
While all lakes studied had some bare rock plus dry tundra, this landscape
classification was more common (40-90%) for the watersheds of northern lakes in GAAR.
The notable exceptions were Tulilik Lake, which, surrounded by wetlands, had a
somewhat low percentage (33%) for a northern lake; and Walker Lake, which, with a lot of
mountainside in its watershed, had a high percentage (60%) for a southern lake (Table 2).
Moist tundra plus sedge classification was more prevalent in northern lakes
(10-66%) than southern, where it was often not measurable (0-9%). An exception was
Summit Lake (5%), a northern lake with only a small proportion of moist tundra and sedge.
This lake was at the highest altitude of all studied and was surrounded by mountains of
bare rock. Floodplain forest and deciduous brush had a completely disjunct distribution.
Northern watersheds had 5% or less of this classification, and southern watersheds had
30-50% (Table 2). Also, spruce and lichen plus black spruce with moss classification was
completely missing from northern watersheds but represented 10^45% of southern
watersheds (Table 2). Therefore, with a few exceptions, southern lakes' watersheds were
dominated by floodplain forest, deciduous brush, spruce with lichen, and black spruce
with moss vegetation. Northern lakes' watersheds were mostly dominated by bare rock
and dry tundra and moist tundra and sedge.
Profiles
Lakes were mainly sampled once per year in summer. Preliminary sampling by the NPS
was conducted in late summer 1 991 ; sampling for this project in 1 995 was about a week
earlier in the season than in 1992 and 1993. However, since the investigator had week-
long experiences at Walker Lake in 1 988 Gones et al., 1 990) and Itkillik Lake in 1 989
(LaPerriere and Jones, 1 991 ), physical and chemical lake profiles (Figures 2-1 5) taken only
once per year still yielded much information.
Thermal conditions in these lakes are somewhat unusual and interesting. Lakes to
the north in GAAR, and coincidentally at higher altitude (>1000 m), did not summer
stratify. Shallower lakes, even those located low and south in GAAR, also probably do not
thermally stratify when not ice covered. In the north, we have evidence that this is caused
10
by frequent, strong winds. When we arrived at Itkillik Lake in 1 989 (8 July) it was
apparently starting to slightly stratify (Figure 5), but just days later (1 1 July), strong winds
arose and the lake mixed to the bottom (Figure 5). Lakes of this thermal condition are
classified as discontinuous cold polymictic (Lewis, 1983). Hobbie (1973) had classified all
arctic lakes as continually mixing. The extra heat entering these lakes must add to
productivity of aquatic organisms. Deep lakes south of the Brooks Range apparently
stratify, which Hobbie (1 973) thought a rare event for arctic lakes.
Temperatures colder than 4°C, the temperature of the maximum density of water,
were found deep in several of the southern lakes in 1992 (Minakokosa, Narvak, Nutuvukti,
Takahula, and Walker; Figures 15, 8, 9, 12, and 14), and this condition was found every
time measured in Takahula (Figure 12). Therefore, Takahula may be a monomictic lake,
overturning only in autumn. The cold hypolimnion is likely due to missed vernal overturns
(Gosink and LaPerriere, 1986; LaPerriere, 1981) during years in which the previous
autumnal overturn continued until the water was colder than 4°C before surface freezing
occurred. Arctic lakes do not warm significantly during winter from back radiation from
the sediments as temperate lakes do (Hobbie, 1973). The vernal overturn is missed
because summer stratification begins and strengthens under the ice, and there are
insufficient winds at ice-off to overturn the lake (LaPerriere, 1 981). Another explanation for
cold, hypolimnetic waters being less than 4°C in summer might be the discharge of cold
groundwater in the basins. Addition of this cold groundwater may be a deep event. We
saw evidence of this in 1 988 (Figure 1 3), measuring at three different depths in a cove of
Walker Lake where water colder than 4°C was sensed deep in the center of the cove.
Monitoring of temperature through the year would be necessary to fully explain this
anomalous thermal phenomenon.
In 1993, we conducted our measurements during and after an unusual arctic heat
wave that caused the 12 July air temperature to reach 34°C at Selby Lake where we were
sampling phytoplankton and periphyton. During the synoptic survey 16-21 July 1993,
maximum surface temperatures were measured: 14.5°C at Agiak, 1 5.2°C at Amiloyak,
11°C at Chandler, 14°C at Itkillik, 16.3°C at Kipmik, 1 8°C at Matcharak and Narvak lakes,
23.4°C at Nutuvukti, 21 .5°C at Selby, 1 4.2°C at Summit, 1 8.5°C at Takahula, and 20°C at
Walker. Therefore, Hobbie's (1973) rule that arctic lakes never warm above 15°C was
violated, even by more northern lakes (Kipmik and Matcharak) in GAAR. Near-bottom
water temperatures for July in some of the polymictic lakes were also highest in 1 993:
1 0°C at Agiak, almost 1 2°C at Amiloyak, 8°C at Chandler, and nearly 1 4°C at Itkillik. In
other years, about 6°C was typical of Agiak and Chandler lakes.
11
Dissolved oxygen conditions in these lakes were usually orthograde; that is,
increasing with decreasing temperatures at depth, following the ideal gas law. When
vernal overturns were apparently missed in 1992, however, some oxygen depletion was
seen near the bottoms of some of the otherwise dimictic lakes: Nutuvukti (Figure 9) and
Minakokosa (Figure 15). Nutuvukti receives water from a peatland, which is probably
anaerobic. This phenomenon might also fit the hypothesis of anomalously cold,
hypolimnetic summer water resulting from intrusion of cold groundwater. Such meltwater
would probably be deoxygenated from contact with soils anaerobic due to decomposing
soil organic matter. Also note that where Takahula Lake had an anomalously cold
temperature at and near 50 m on 21 August 1991 (Figure 12), dissolved oxygen was quite
reduced (Figure 12). However, deoxygenation at depth may also be due to respiration of
deep algal peaks in some of these particular lakes (this will be discussed with the nutrients
and plankton results later).
Clinograde oxygen profiles (those in which concentrations decrease at depth
despite colder temperatures) in polymictic lakes, such as at Kipmik Lake in mid-August
1 991 (Figure 6) and in Matcharak Lake in 1 993 and 1 995 (Figure 7), may be due to the
die-off and settling of rich plankton, or to the phenomenon described by Hobbie (1973)
wherein cooling, sinking water from the shallows in autumn is deoxygenated by contact
with anaerobic bottom sediments. It may also be due to contact of runoff with organic soil.
Subsurface peaks of oxygen were also seen around the thermoclines of some dimictic lakes
(Takahula and Walker). These were probably due to algal photosynthesis at deep, peak
chlorophyll concentrations, which will also be discussed later in the nutrients and
plankton section.
Plankton algae may also be responsible for elevations of pH seen near the surface
of many lakes (Agiak, Chandler, Kipmik, Matcharak, Minakokosa, Summit, Takahula,
Tulilik, and Walker) and at all depths of the shallow Pingo Lake. All the lakes studied have
relatively low conductivity [40-450 microSiemens per centimeter (uS/cm)] and alkalinity
and are, therefore, likely to show an increase in pH with active photosynthesis (Wetzel,
1 983). Conductivity was lower in 1 995 in Agiak (Figure 2), Chandler (Figure 4), and
Summit lakes (Figure 1 1 ) when measured earlier than in other years, probably due to
recent ice- and snowmelt in their basins. Oxidation-reduction potential (ORP) varied
between about 200 and 300 millivolts (mV) in these lakes; in other words, they were
always in oxidizing conditions measured at all depths in the early summer.
12
Major Ions
Most lakes of GAAR are so-called calcium carbonate lakes because the dominant cation is
calcium and the dominant anion is bicarbonate (Table 3). This was said to be typical of
arctic lakes (Kalff, 1968). However, there were two unusual lakes sampled in this synoptic
survey. Pingo Lake, at the head of the Noatak watershed, was a magnesium-calcium
bicarbonate lake, and Chandler Lake, near the head of the Chandler River drainage, was a
calcium-sulfate bicarbonate lake. The condition of Pingo Lake is likely due to local
lithography. Chandler Lake was measured to have an alkalinity to calcium-plus-
magnesium ion ratio of 0.6, below the normal range (0.8-1 .2) of pristine lakes unaffected
by acid precipitation (Schindler, 1988). Acid precipitation is not a likely cause of
Chandler's unusual chemistry, however, because Amiloyak Lake upstream in the
watershed is an ordinary calcium-carbonate lake. It was believed that the high sulfate in
Chandler Lake comes from the presence of reduced sulfur rocks in the lake's watershed,
though this was not established.
In this study, lakes did not become more saline (higher total major ions) at lower
altitudes as was true of the subarctic lakes studied at Katmai National Park and Preserve
(LaPerriere, 1996). At Katmai, the lakes studied were connected along two major
drainages, so the salinity was expected to increase down gradient. At GAAR, the lakes lie
on many drainages, and only Selby and Narvak, and Amiloyak and Chandler, are
connected to each other. Surprisingly, Amiloyak was not a sulfate lake, while Chandler,
lower in the drainage, was dominated by sulfate. Narvak and Selby were quite similar
chemically and are even considered by some to be a single lake with a narrow channel
between two basins.
Also, in contrast to Katmai findings, none of the lakes studied had a high proportion
of chloride. In fact, it was not measured after the first two years, when it was found below
the method's detection limit [0.1 milligrams per liter (mg/L)] in all the lakes sampled. It
may be measurable in lakes to the far north in GAAR, but the close ion balances (Table 3)
of Itkillik (where it was measured below detection in 1 993) and Kurupa lakes, the farthest
north lakes studied, do not imply that chloride is a missing major ion. Evaporite rocks,
likely to be sodium rich, are not mapped in any of the studied basin. Sodium (logged), in
fact, varies only with the major ion (log) magnesium (i^adj = 0.552, p = 0.0006). Therefore,
the Beaufort Sea, and especially storms moving southward from the Beaufort Sea, do not
seem to move much sodium chloride into the northernmost lakes measured. The
phenomenon of sodium chloride dominance is, however, known to happen to lakes on the
Alaska North Slope (Kling et al., 1 992), to the north of GAAR, but reported only in small,
shallow (<0.8 m) lakes near the ocean.
13
Among the study lakes, calcium varied directly with alkalinity (r2AD. = 0.90, p =
0.0000) as would be expected in lakes that are mainly calcium carbonate, wherein the
major component of alkalinity is the bicarbonate ion. Lakes with limestone in the
watershed, or in the source area of glaciers that entered the watershed (Dr. David
Swanson, 1997, personal communication) (Itkillik, Matcharak, Pingo, Takahula, and
Walker), had higher calcium concentration [33.5 ± 12.4; (x ± 95% confidence interval
versus 8.05 ± 3.14)] and higher alkalinity (91 .5 ± 51.6 versus 22.3 ± 1 1.2). Magnesium, for
most lakes (except Pingo, where it was equally dominant with calcium, as mentioned
earlier) was the second most dominant cation. Therefore, as expected, magnesium and
calcium varied together (r2ADj = 0.526, p = 0.0009; Figure 1 6), and magnesium varied with
alkalinity (r^pj = 0.775, p = 0.0000) like calcium. The northcentral lakes in GAAR (Agiak,
Amiloyak, Chandler, Tulilik, and Kurupa) as well as Pingo, which is to the west of these,
have relatively more magnesium versus calcium than the rest of the lakes (Figure 16).
Trace Metals
The method of ICP spectrophotometry used to measure the major cations that were
discussed earlier in this report also measured the trace metals (Appendix B). Trace metals
detected in particular lakes all three years were few: barium (Ba), copper (Cu), iron (Fe),
manganese (Mn), nickel (Ni), silicon (Si), strontium (Sr), vanadium (V), and zinc (Zn) (Table
4). Copper, zinc, and nickel, measured in Chandler Lake in 1995 (Appendix B), often
occur together in sulfide ore bodies. Such an ore body, as mentioned before, may be
present in the Chandler Lake watershed. Of these metals, only copper was found above the
freshwater criteria (USEPA, 1984) set to prevent acute and chronic harm to organisms.
However, the only year in which this occurred was 1995 when the lake had just cleared of
ice. Turbid conditions from recent snowmelt that year (Appendix C) also were associated
with measurable aluminum, vanadium, and zinc in Chandler Lake and measurable
aluminum in Kurupa and Summit lakes. Aluminum is a dominant component of some
clays.
Iron (log) varied directly with (log) color (r2ADJ = 0.805, p = 0.0000). Therefore, the
brown color of these lakes cannot probably be entirely attributed to humates, but some is
undoubtedly from iron and its oxides (Wetzel, 1983). Additionally, Secchi disk depth was
shallower in response to (log) iron (r2ADj = 0.741, p = 0.0000). This inverse relationship
between iron and Secchi depth probably occurred because humates act as complexing
agents that keep iron in the water column, and the associated color of both the humates
and the iron decreased Secchi transparency.
14
As the altitude of the lakes increased, the (log) manganese also increased (r^rjj =
0.612, p = 0.0003). Manganese (logged) also varied directly with the proportion (arcsine1/2)
of bare rock plus dry tundra in the watershed (r2ADj = 0.586, p = 0.0003) and inversely
with the proportion (arcsine1'2) of floodplain forest and deciduous brush in the watershed
(r2ADj = 0.522, p = 0.0009). Therefore, manganese was higher in the watersheds of the
northern lakes of GAAR, which were at increased altitude and likely to have high amounts
of bare rock and dry tundra and lower amounts of floodplain forest and deciduous brush.
Strontium (logged) varied directly with the (log) total major ions (i"2^ = 0.645, p =
0.0001) and with (log) alkalinity (r2ADJ = 0.599, p = 0.0003). These relationships probably
demonstrate that the forces, particularly of weathering, that release the major ions also
release strontium into these lakes.
Nutrients and Phytoplankton
All of the studied lakes would be classified as oligotrophic on the basis of the measured
total chlorophyll biomass estimates of the phytoplankton (Nurnberg, 1996), which were
less than 3.5 ug/L for all measurements of all lakes (Table 5). However, total phosphorus
measurements (Table 5) exceeded the oligotrophic-to-mesotrophic limit of 10 ug/L
(Nurnberg, 1996) once each in Amiloyak, Matcharak, Kurupa, and Summit lakes. The
exceedances in Kurupa and Summit lakes occurred in 1995, when we sampled about a
week earlier than the other two years, and we could see the particulates caused by rock
material that entered with the recent snowmelt acting as turbidity. Adsorbed phosphorus
on the rock material would be measured as total phosphorus but might quickly sediment
out of the water column.
The total nitrogen limit of 350 ug/L for the oligotrophic-mesotrophic boundary
(Nurnberg, 1996) was exceeded in 1992 and 1993 in Matcharak Lake and once each in
Narvak, Pingo, Takahula, and Tulilik lakes (Table 5). We cannot tell if this is a common
occurrence in Pingo and Tulilik lakes because we sampled each only once.
As mentioned earlier, Matcharak Lake did have deoxygenation of its deeper water.
Because it is richer in nutrients, it may also have more phytoplankton than the other lakes.
This could happen as a thin, deep peak of plankton algae that might be missed in discrete
sampling and underestimated in integrated sampling. However, there was also some
evidence of late-summer deoxygenation of nearby Kipmik Lake (in 1991), which is much
less rich in major ions and nutrients. The low oxygen concentration, however, was
measured in a small, deep hole near an inlet and may be local and due to allochthonous
plant materials being washed in and decomposing there.
15
Among these lakes, total phosphorus was comparatively low (4-6 ug/L) in the lakes
south of the Brooks Range (Table 6), varying (as the log) inversely with the proportion
(arcsine,/2) of floodplain forest plus deciduous brush {r2AD^ = 0.480, p = 0.0018) in the
watershed (Table 2). There was not a general relationship between total phosphorus and
latitude among all the lakes. Manganese (log) and total phosphorus (log) varied together
(r2AD. = 0.671 , p < 0.0001 ), which is an indication that total phosphorus might also (like
manganese) be associated with the bare rock proportion in the watersheds, because it was
at somewhat higher concentrations at higher elevations (altitude) in GAAR (r^™ = 0.462,
p = 0.0023).
The total nitrogen-to total phosphorus (TN/TP) ratio varied for particular lakes from
year to year (Table 5). The ratios for the two years (1 993 and 1 995) when water-column
integrated samples were taken were not more similar than each compared to the ratios for
a particular lake in 1 992 when discrete samples were taken. The lack of similarity of ratios
of 1 993 and 1 995 was possibly due to the approximate one week earlier in 1 995 that the
lakes were sampled compared to 1 992 and 1 993. The multi-year lake average TN/TP ratio
(Table 6) was less than 13, which implies nitrogen limitation (Smith, 1979), for only
Kurupa (1 2; sampled 1 995 only) and Summit (1 1 ) lakes. The multi-year average ratio
(Table 6) was above 21 , which implies phosphorus limitation (Smith, 1 979), for Amiloyak
(24), Chandler (27), Itkillik (35), Kipmik (27), Matcharak (38), Minakokosa (78), Narvak
(90), Nutuvukti (57), Pingo (48), Selby (75), Takahula (61), Tulilik (62), and Walker (77)
lakes. Agiak Lake had a two-year average ratio of 1 7, which means it may be limited by
nitrogen or phosphorus (Smith, 1979).
We have evidence from nutrient stimulation bioassay experiments (NSEs) that, as
expected, Walker (Jones et al., 1 990), Selby (LaPerriere et al., 1 998), and Narvak lakes,
which all had very high TN/TP ratios, were phosphorus limited when we measured them
(Table 7), as was Chandler in 1995, which had a much lower TN/TP ratio (14). However,
we have NSE evidence that Agiak (TN/TP = 1 2 in 1 995), Itkillik (36), Kipmik (22),
Matcharak (36), and Summit (6) lakes were nitrogen limited early in summer 1995 (Table
7). We also have earlier NSE evidence that Itkillik Lake was nitrogen limited in 1989 (Table
7) (LaPerriere and Jones, 1 991 ). Therefore, perhaps a TN/TP ratio of up to 36 can be
associated with nitrogen limitation in these lakes. Excluding Chandler Lake, where only
one experimental set was retrieved, multi-year ratios above 75 were shown by experiments
to be associated with phosphorus limitation. Much more experimentation and multiple
nutrient measurements over the open water season to allow calculation of seasonal
averages would need to be done to fully determine the pattern of nutrient limitation in
GAAR.
16
The multi-year average TN/TP ratios (Table 6) of these lakes decreased with altitude
(r2ADJ = 0.880, p < 0.0001) and with latitude (r^j = 0.688, p < 0.0001), again showing
that phosphorus was relatively higher in the northern lakes (in the Brooks Range) and that
nitrogen was relatively higher in the southern lakes. The ratio fell with increasing
proportion (arcsine1/2 transformed) of bare rock plus dry tundra in the watershed (r2ADj =
0.571, p = 0.0004), typical of northern lakes, and increased with increasing proportion
(arcsine1/2 transformed) of floodplain forest plus deciduous brush (r^Qj = 0.544, p =
0.0007) and of black spruce plus moss (i^adj = 0.61 3, p = 0.0002), typical of southern
lakes. To sum this up, TN/TP is higher with increased land plant biomass in the watershed.
Among all these lakes, plankton biomass as total chlorophyll was not related to
total phosphorus or total nitrogen concentrations. This may be due to some of the lakes
being phosphorus limited and others nitrogen limited. These data do not allow definitive
separation of all the lakes into these two classes. Another factor that probably affects the
nutrient-chlorophyll relationships is the presence of deep peaks of phytoplankton. We had
evidence of these deep peaks in several lakes (Table 8), both lakes that stratified and those
that mixed throughout summer (Kipmik and Matcharak).
When discrete-depth algal biomass data that demonstrated deep algal peaks (Table
8) were averaged and compared to data obtained with the integrating tube from the same
lakes in 1 993 and 1 995 (Table 5), the values were not close to each other. Thus, the
sampling scheme used in 1 992 was probably not adequate to characterize the water
column, perhaps because peak algal biomass was not consistently at the Secchi depth or
twice the Secchi depth and, therefore, was not necessarily sampled. Algal peaks were
found in both polymictic and stratified lakes and thus were not necessarily associated with
a thermocline.
The peak biomass of plankton algae (as total chlorophyll) was often found at quite
low light levels, varying between about 1% and about 4% (Table 9). This phenomenon
may be due to low-light adapted algae that bloom under the ice in the spring and seek a
lower position with reduced light after ice-off, rather than being associated with the barrier
to sinking of a thermocline. Measurements of growth of these deep algae need to be made
to help determine why they congregate at these deeper depths.
Light Conditions
While these lakes (Table 10) were not as clear as the lakes of Katmai National Park and
Preserve (LaPerriere, 1 996), they were among the clearest in the nation in summer 1995,
measured as Secchi depth (Carlson, 1996). Light penetration, measured as the 1% light
depth, was less in GAAR lakes (x = 12.1 m versus 29.2 m at Katmai). Correspondingly,
17
turbidity and apparent (unfiltered) color (Table 10) were higher in GAAR lakes. The
relatively high turbidity and apparent color values for Kurupa and Summit lakes were due
to the early sampling of 1 995 (Appendix C) just after snowmelt, when both lakes were
apparently inundated with rock flour. Turbidity is probably high in Kurupa Lake through
the ice-free season because it has a glacial source. Turbidity was also higher in Summit
Lake in 1 993 than in the other lakes measured that year (Appendix C), when we observed
a massive debris flow that eventually entered the lake while we were sampling, just after a
thunderstorm had ended. Turbidity in the lake at that time may have been due to residual
suspended material from snowmelt, as well as from debris flows caused by rainstorms. In
this massive national park there are no weather stations; therefore, one could not know the
weather with certainty without observing it directly.
Among these lakes, not only was there no relationship found between nutrients and
plankton algal biomass (as total chlorophyll), but there was also no relationship found
between plankton algal biomass and Secchi depth. Both relationships are typical of most
large lake regions (Carlson, 1977; Numberg, 1996). Secchi depth, however, had a strong
inverse relationship to apparent water color (i^adj = 0-789, p = 0.0000), which may
include some effects of turbidity because apparent color samples are not filtered. Even so,
this was undoubtedly mostly non-plankton turbidity because there was no relationship
found between algal plankton and Secchi depth. Therefore, in these lakes, it was color and
associated turbidity that scattered light, shallowing Secchi depths. This is expected in
colored, turbid systems (Koenings and Edmundson, 1991). Color and iron (both logged)
were strongly related to each other (i^adj = 0-805, p = 0.0000), so Secchi depth also varied
inversely with iron concentration. Therefore, as said before, much of the color in these
lakes may be iron oxides and, perhaps, iron complexed by humates.
The ratio between the 1% light depth and the Secchi depth (Table 1 1) varied
widely rather than narrowly around the rule of thumb (Kirk, 1 994) of a ratio of 3. The
highest ratios appeared to be associated with relatively low Secchi depths caused by
scattering materials (turbidity) (Table 10). Another rule of thumb, that the 1% light depth is
the lower limit of plant growth (euphotic) zone, may also not hold for these lakes. Many of
these lakes had chlorophyll peak concentrations near the 1% light level, indicating that
maximum plankton algal biomass was near there (Table 9).
Periphyton
Periphyton (benthic algae growing on rocks) was only sampled at Selby Lake (LaPerriere et
al., 1998). Its standing crop measured about equal to the standing crop of phytoplankton.
Local standing crop was higher near colder inlets and higher with higher total nitrogen of
18
the nearby inlets. Periphyton is probably critically important in arctic lakes because the
food chain of these lakes may be quite dependent on benthic algae (O'Brien, 1 997).
Zooplankton
All of the lakes sampled in 1993 wherein zooplankton were identified and counted, as
well as massed (Table 12) as in the other two years, had cladocerans (water fleas) (Table
13). Therefore, these lakes would be classified among arctic lakes of the highest trophic
status (but still oligotrophic) according to Hobbie (1 973).
Low counts of cladocerans per cubic meter were recorded for Agiak (6), Chandler
(6), and Nutuvukti (8) lakes. No rotifers were counted from Chandler or Nutuvukti lakes.
This may have been an artifact of sampling if the net mesh (0.001 cm) was too large to
capture smaller rotifers that may have been present. Hobbie (1 973) concludes that rotifers
are in all arctic lakes, even those of the lowest trophic state.
Copepods (Table 1 3) dominated most of the zooplankton counts and were mostly
calanoids (Table 14) when identifiable (i.e., not nauplii or copepodites too small to
identify). Therefore, copepod counts were correlated with average ash-free masses of
zooplankton among these lakes (r^DJ = 0.738, p = 0.0002). Cyclopoid copepods were not
found in most of these lakes (Table 14).
Zooplankton standing crop (Table 12) was similar for a lake between the years
sampled if the depth of the vertical hauls was similar. If the haul depth was different,
because the lake was sampled at a different station, the zooplankton sampling crop
estimates (as mass per water volume) were different. This probably results from an uneven
distribution of zooplankton with depth during the day in at least some of these lakes. This
phenomenon is commonly found in lakes. Note that Pingo Lake was not sampled for
zooplankton in 1 992, the only year it was sampled, because it was too shallow compared
to the length of the net. Thick zooplankton, including amphipods (scuds), were, however,
visible in Pingo Lake.
Lake Productivity
In general, shallow lakes are more productive than deeper lakes (Rawson, 1952) because
nutrients and plankton are kept circulating rather than settling into the depths where they
are trapped and light becomes limiting. Three GAAR lakes were not mapped — Pingo,
Tulilik, and Summit — but were assessed as shallow. Estimates of the mean or average
depths of those three lakes were calculated by assuming the anchor depth was the deepest
spot and by dividing that depth by 2.4, which was the average quotient of the maximum
19
depth divided by the mean depth for the other 1 3 lakes. Besides the three unmapped lakes,
Amiloyak, Agiak, and Itkillik lakes were also shallow (Table 15).
Lakes are also known to vary in productivity with the amount of salts they contain,
which can be measured as conductivity, total dissolved solids, or alkalinity (Rawson,
1951). When the lakes were ranked from high to low alkalinity, the six saltiest lakes were
Pingo, Takahula, Itkillik, Matcharak, Tulilik, and Walker (Table 15).
An empirical relation between fish yield and both the lake morphometry, as mean
depth, and saltiness, as total dissolved solids, was developed and tested in many (mostly
temperate) regions (Ryder et al., 1974). This relation is called the morphoedaphic index
(MEI) and is here calculated by dividing total ions (mg/L) by the particular lake's mean
depth. The estimated MEI of lakes of GAAR (Table 1 5) is higher for Pingo, Itkillik, Tulilik,
and Matcharak lakes, which implies they produce more fish. Pingo Lake probably does not
have fish because it is so shallow it freezes to or very near the bottom. We observed large
amphipods, which indicated the absence offish.
The only study lakes in GAAR where fish densities have been evaluated are
Amiloyak and Chandler (Troyer and Johnson, 1 994), Walker (Johnson and Troyer, 1 994),
and Itkillik (Patricia Rost, Chief of Natural Resources, GAAR, personal communication).
The fish densities were from population estimates and are not yield, which is fish
harvested. However, lakes with higher calculated MEI values (Itkillik and Amiloyak) had
higher density estimates for top predator fish (lake trout and Arctic char). Lower MEI values
for Chandler and Walker lakes were associated with lower density estimates of those fishes
(Figure 17).
To use growth of plankton algae and especially zooplankton to evaluate the
productivity of these lakes would require expensive and difficult efforts repeatedly over the
entire growing season. However, standing crop, in situations where grazing by the next
higher trophic level is not intense, may be a good indicator of productivity.
Tulilik, Itkillik, Matcharak, and Amiloyak lakes ranked as the four highest when
standing crop as ash-free dry weight of zooplankton (Table 12) was used as an indicator of
productivity, which seemed acceptable for these arctic lakes where there are no fish that
graze exclusively on zooplankton.
Standing crop of planktonic algae (as chlorophyll) was higher in Pingo and
Matcharak lakes, but also in Kipmik, which had a low MEI value. Because zooplankton
graze on planktonic algae, the high standing crop of algae in Kipmik Lake may be an
artifact of lower grazing pressure there by fewer zooplankton than in other lakes.
Therefore, standing crop of algae is probably not a good indicator of productivity for all
these lakes.
20
John River
The flows of the two tributaries of the John River through Anaktuvuk Pass (Contact Creek
and Little Contact Creek) were equal to about half the estimated flow of the John River
(Table 1 6), which probably indicates that the John River and its tributaries (Figure 1 ) are
gaining groundwater or hyporheic flow between the sampling stations.
The characteristics of the three sampling stations indicate they were similar when
measured both times, with Little Contact Creek having the highest conductivity (or
saltiness), Big Contact Creek the lowest conductivity, and the John River an intermediate
conductivity (Table 1 6). These waters were of the normal calcium carbonate type (Table
17).
Big Contact Creek and the John River are chemically similar, and Little Contact
Creek is a little more concentrated with regard to the major positive ions (Table 18 and
Appendix D). No fecal coliform bacteria were consistently found in any of these streams at
the time of sampling (at or above 2 per 1 00 mL or at or above 1 .1 colonies per 1 00 mL).
Total coliforms (Table 19) were slightly higher in the John River (18.4 ± 4.0 colonies/100
mL; n = 3) than in either Big Contact Creek (5.2 ± 1 .6 colonies/1 00 mL; n = 3) or Little
Contact Creek (3.6 ± 1 .4 colonies/1 00 mL; n = 3). Three of six samples from the John River
had a measurement of total petroleum hydrocarbons above the method detection limit of
0.4 mg/L (Table 20). A much more intense sampling effort on these streams with more
sensitive methods for hydrocarbons would be necessary to detect any contamination by
bacteria or petroleum products.
21
Future Research
• The cause of the unusually cold hypolimnia at times on the south slope of the Brooks
Range should be investigated. Because Takahula Lake had a cold hypolimnion every
time profiled, it should probably be the lake studied.
• The relative importance of phytoplankton, periphyton, and vascular aquatic plants
should be investigated by measuring standing crop and growth over the growing
season for these three communities in several lakes.
• The viability of plankton algae in deep peak concentrations should be measured by
growth experiments conducted by incubating the algae at depth over time.
• Light limitation of plankton algae should be studied by growth experiments.
• Nutrient limitation of plankton algae should be studied repeatedly over the growing
season in several lakes that appear from TN/TP ratios to be nitrogen or phosphorus
limited.
• The source of the high proportion of sulfate and any association with trace metals in
Chandler Lake should be identified.
• The importance of benthic algae and vascular aquatic plants to primary consumers
should be investigated.
• An evaluation of the distribution of benthic invertebrates in GAAR lakes and streams
should be conducted.
• The importance of the hyporheic zone should be investigated in GAAR streams with
deep gravel beds.
• The relative productivity of GAAR streams should be studied.
22
Acknowledgments
This project was funded by the Water Resources Division of the National Park Service,
proposed by Judy Alderson of the Alaska Regional Office, NPS. Patricia Rost, Chief of
Resources for the Park, facilitated and aided our work. Nancy Deschu of the Alaska
Regional Office participated in and encouraged the project. Gary Vequist of the Alaska
Regional Office administered the monies. Dr. John R. Jones and Bryn Tracy participated in
the field work, and Dr. Jones headed up the nutrient and phytoplankton studies. Brady
Christoph helped with the periphyton study at Selby Lake in 1993. Scott Smidt helped with
data reporting in 1 994, and he and Wiebke Boeing helped with field work at Anaktuvuk
Pass in 1994. Lynn Mattes counted and identified 1993 zooplankton samples as an
undergraduate honors project. Park pilots Ed Forner and Buster Points, and the pilots of
Brooks Range Aviation, provided safe, reliable transportation. Dr. David Swanson provided
landscape analysis of the lake watersheds. Kathy Pearse wordsmithed this document, and
Betsy Sturm drafted most of the figures.
23
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28
Glossary
Accuracy
Alkalinity
Amphipods
Anion
Attenuation
closeness of measurements to the true value
the sum of the negative ions of the salts of the weak acids; in
freshwater usually mainly bicarbonates, carbonates, and carbon
dioxide
small Crustacea that are laterally compressed with many-segmented
bodies
negatively charged ions
to lessen in amount
Bathymetry
Benthic
Bioassay
the science of measuring the depths of water bodies
attached to or associated with the bottom sediments
an experiment in which substances are added to measure an
induced change compared to the results of no addition
Cation
Chlorophyll
Coliform bacteria
Conductivity
Copepodite
Copepods
positively charged ion
the enzyme that plants use to capture light energy
indicators of sewage or animal fecal pollution
ease of passage of electrons through water because of salt content
juvenile copepod
crustacean microzooplankton that swim with their second antennae
and do not have jointed feeding appendages
Detection limit
Dimictic
the lowest value that can be measured reliably
mixing twice during the year usually in spring and autumn
Empirical
Epilithic
a relationship developed from the data
growing attached to rocks
Fluorometer
Formalin
instrument that induces and measures fluorescence of certain
substances
38% formaldehyde
Hu mates
Hypolimnion
break-down products of vegetation
cold, deep water in a stratified lake during summer
29
Hyporheic
Irradiance
the zone of flow of a stream that is within the sediments and above
the groundwater
the amount of light or other radiant energy hitting a given area of
surface
Leachate
Lithography
Major ions
Mesotrophic
Monomictic
Morphometry
Nauplii
Nephelometer
Nutrients
water that has filtered down through the soil and then might enter a
surface waterbody
rocks near the ground surface
in fresh waters — calcium, magnesium, sodium, potassium,
carbonate, sulfate and chlorides
medium in concentrations of nutrients and resulting growth of
higher trophic levels — plants and animals
mixing only once during a season or year
geometric measurements
larval copepods
instrument for measuring the turbidity of water
essential substances for organismal growth
Oligotrophic low in concentrations of nutrients and resulting growth of higher
trophic levels - plants and animals
Overturn complete mixing of a water column top to bottom
Oxidation-reduction potential proportional to the equivalent free energy change per mole
of electrons associated with a given chemical reduction
Periphyton
Permafrost
Photosynthesis
Phytoplankton
Plankton
Polymictic
Precision
Primary standard
attached algae that grow on rocks
permanently frozen ground that may be ice rich or ice free
production of organic substances from inorganic ones using sunlight
plants such as algae that float in the water column
plants and animals that float and have little control of their position
in the water column
water column mixes several times during a season
repeatability of measurements
chemical used to test the accuracy of quantitative chemical methods
30
Reagent
Respiration
Rotifers
Runoff
chemical used to detect or measure another substance or to cause a
chemical change
breakdown of organic substances producing carbon dioxide and
water
microscopic animals that feed with cilia or by engulfing particles
precipitation that is not intercepted but that runs across the surface
into waterbodies
Secchi transparency clarity of water as measured by a standard Secchi disk on a depth-
calibrated line
Spectrophotometer instrument that selects a wavelength of light and measures its
absorption through colored substances
a known amount of a chemical added while measuring that
chemical in a sample to measure percent recovery
measure of biomass of a plant or animal or trophic level at a
particular time
water column becomes resistant to mixing because of heat or salt
content
sampling (lakes) sufficiently to present the general conditions
Spike
Standing crop
Stratify
Synoptic study
Tared
Thermocline
Trophic status
Turbidimetric
Vernal
pre-weighed container for weighing contents (or its weight may
have been zeroed)
a density gradient caused by differing temperatures
richness of a waterbody for nutrients and resultant plant and animal
growth
using a turbidimeter
of the spring
Zooplankton
animals (usually microscopic) that float in the water column
31
Table 1 . The study lakes, Gates of the Arctic National Park and Preserve.
Maximum
Surface Area
Volume
Mean Depth
Depth
Lake
(km2)
(m3 x106)
(m)
(m)
Agiak
1.5
7.8
5.2
16
Amiloyak
1.1
4.1
3.9
10
Chandler
12.8
181.
14.1
22
Itkillik
3.9
23.
5.8
13
Kipmik
2.9
25
8.6
45
Kurupa
4.6
67
14.6
37
Matcharak
2.8
35
12.5
25
Minakokosa
3.2
114.
35.5
54
Narva k
8.7
543
62.4
114
Nutuvukti
16.2
319.
19.7
49
Pingo
0.7
a
—
—
Selby
9.9
145.
14.6
33
Summit
0.4
—
—
—
Takahula
1.7
55
32.3
55
Tulilik
0.2
—
—
—
Walker
37.5
2297.
61.4
122
a Dash means bathymetric map not available.
32
Table 2. Geomorphic and landscape characteristics of lakes of Gates of the Arctic
National Park and Preserve.
Lake
Altitude (ft)
Latitude
(degrees)
Longitude
(degrees)
Watershed Area (km2)
Agiak
3158
68.08
152.95
51.4
Amiloyak
3182
68.11
152.86
26.9
Chandler
2913
68.22
152.71
341.2
Itkillik
2235
68.40
149.92
26.3
Kipmik
2429
67.95
156.13
43.6
Kurupa
3035
68.34
154.64
173.5
Matcharak
1648
67.75
156.21
32.2
Minakokosa
451
66.93
155.02
94
Narvak
475
66.93
155.63
234.3
Nutuvukti
631
66.98
154.70
75.9
Pingo
1771
67.67
155.41
6.1
Selby
475
66.87
155.68
280.9
Summit
3520
68.07
150.46
4.4
Takahula
810
67.35
153.66
5.5
Tulilik
1821
68.13
154.12
3.2
Walker
637
67.13
154.38
523.6
% Floodplain
% Spruce
Forest and
and Lichen
% Bare Rock
% Moist Tundra
Deciduous
and Black
Lake
and Dry Tundra
and Sedge
Brush
Spruce and Moss
Agiak
76
15
0
0
Amiloyak
70
30
0
0
Chandler
70
25
0
0
Itkillik
48
52
0
0
Kipmik
66
33
0
0
Kurupa
90
10
0
0
Matcharak
43
53.5
3.5
0
Minakokosa
15
0
38
45
Narvak
20
9
41
30
Nutuvukti
5
10
50
35
Pingo
83
17
0
0
Selby
20
9
41
30
Summit
90
5
5
0
Takahula
33
0
50
17
Tulilik
33
66
0
0
Walker
60
0
30
10
33
Table 3. Major ion balances, lakes of Gates of the Arctic National Park and Preserve.
Agi
iak
Am
iloyak
Chandler
(mg/L)
(meq/L)
(mg/L)
(meq/L)
(mg/L)
(meq/L)
Ca
2.00
0.100
3.72
0.186
7.60
0.379
Mg
1.00
0.082
2.08
0.171
4.39
0.361
Na
0.33
0.014
0.63
0.027
2.13
0.093
K
0.12
0.003
<0.05
<0.001
0.384
0.36
0.009
Cations
0.199
0.842
HCO3
5.6
0.112
14.2
0.284
21.6
0.432
S04
1.0
0.021
9.0
0.187
22.0
0.458
CI
<0.1
<0.004
<0.1
<0.004
<0.1
<0.004
Anions
0.133
0.471
0.890
Total Ions
0.322
0.855
1.732
Itkillik
Ki
pmik
Ku
rupa
(mg/L)
(meq/L)
(mg/L)
(meq/L)
(mg/L)
(meq/L)
Ca
37.0
1.846
2.98
0.149
13.7
0.684
Mg
2.08
0.483
0.95
0.078
8.25
0.679
Na
0.63
0.023
0.53
0.023
3.60
0.157
K
0.51
0.013
<0.05
<0.001
0.250
0.45
0.012
Cations
2.365
1.532
HCO3
101.3
2.024
7.90
0.158
47.1
0.941
S04
6.0
0.125
0.60
0.012
28.3
0.589
CI
<0.1
<0.004
<0.1
<0.004
<0.1
<0.004
Anions
2.149
0.170
,
1.530
Total Ions
4.514
0.420
3.062
Matcharak
Minakokosa
Narvak
(mg/L)
(meq/L)
(mg/L)
(meq/L)
(mg/L)
(meq/L)
Ca
35.1
1.752
9.37
0.468
12.8
0.639
Mg
5.57
0.458
1.61
0.132
2.22
0.183
Na
4.93
0.214
0.91
0.040
0.61
0.027
K
0.62
0.016
<0.05
<0.001
0.640
<0.05
<0.001
Cations
2.440
0.849
HCO3
98.3
1.964
16.0
0.320
25.6
0.512
SO4
23.0
0.479
9.0
0.197
20.0
0.416
CI
<0.2
<0.010
<0.1
<0.004
<0.1
<0.004
Anions
2.443
0.507
0.928
Total Ions
4.883
1.147
1.777
Table 3. Continued.
34
Nutuvukti
(mg/L) (meq/L)
Pi
(mg/L)
ngo
(meq/L)
Selby
(mg/L) (meq/L)
Ca
Mg
Na
K
8.63
1.51
0.69
<0.05
21.5
2.30
<0.1
0.431
0.124
0.030
<0.001
25.4
20.1
20.6
<0.5
155.
1.00
<0.1
1.267
1.654
0.896
<0.005
3.817
3.098
0.021
<0.004
3.119
11.90
2.11
0.64
<0.05
23.4
21.0
<0.1
0.594
0.174
0.046
<0.001
Cations
HCO3
SO4
CI
0.585
0.430
0.048
<0.004
0.814
0.468
0.437
<0.004
Anions
0.478
0.905
Total Ions
1.063
6.936
1.719
Summit
(mg/L) (meq/L)
Takahula
(mg/L) (meq/L)
Tulilik
(mg/L) (meq/L)
Ca
Mg
Na
K
3.60
1.30
1.05
0.44
8.40
2.00
<0.1
0.180
0.107
0.046
0.011
48
7.59
0.71
1.10
127.7
23.0
<0.1
2.395
0.626
0.031
0.028
12.30
8.47
2.4
1.3
54.2
1.0
<0.1
0.614
0.697
0.104
0.033
Cations
HCO3
SO4
CI
0.344
0.168
0.042
<0.004
3.080
2.552
0.479
<0.004
3.031
1.448
1.083
0.021
<0.004
Anions
0.210
1.104
Total Ions
0.554
6.111
2.552
Walker
(mg/L) (meq/L)
Ca
Mg
Na
K
21.9
2.59
0.47
0.97
55.1
7.2
<0.1
1.093
0.213
0.020
0.025
Cations
HCO3
S04
CI
Anions
1.351
1.101
0.150
<0.004
1.251
Total Ions
2.602
35
Table 4. Trace metal characteristics (ICP) of Gates of the Arctic samples, as total
recoverable metals. A dash means criterion (USEPA) is not yet set.
Laboratory
Detection
Acute
Chronic
Limit
Criterion
Criterion
Detected
Criterion
Metal
(mg/L)
(mg/L)
(mg/L)
(1992-1995)
Exceedances
Silver (Ag)
0.01
4.1
0.12
Aluminum (Al)
0.02
0.75a
0.087a
Arsenic (As)
0.04
0. 360b
0.190b
Boron (B)
0.02
—
—
Barium (Ba)
0.0034
—
—
Yes
N/A
Beryllium (Be)
0.0005
0.130c
0.0053c
Bismuth (Bi)
0.04
—
—
Cadmium (Cd)
0.002
0.0039d
0.001 1d
Cobalt (Co)
0.01
—
—
Chromium (Cr)
0.01
0.001 6e
0.001 1e
Copper (Cu)
0.003
0.001 8d
0.0012d
Yes
Yes§
Iron (Fe)
0.005
—
1.000
Yes
No
Lithium (Li)
0.002
—
—
Manganese (Mn)
0.002
—
—
Yes
N/A
Molybdenum (Mo)
0.005
—
—
Nickel (Ni)
0.01
1 .400d
0.1 60d
Yes
No
Phosphorus (P)
0.09
—
—
Lead (Pb)
0.04
0.083a
0.0032d
Antimony (Sb)
0.04
0.088f
0.030f
Selenium (Se)
0.04
0.020
0.005
Silicon (Si)
0.005
—
—
Yes
N/A
Tin (Sn)
0.04
—
—
Strontium (Sr)
0.001
—
—
Yes
N/A
Titanium (Ti)
0.002
—
—
Thallium (Tl)
0.08
—
—
Vanadium (V)
0.003
—
—
Yes
N/A
Zinc (Zn)
0.002
0.112
0.103
Yes
No
a pH 6.5-9.
b Arsenic (III).
c Lowest Observed Effect Level.
d Hardness dependent criteria (100 mg/L as CaC03 used).
e Cr (VI).
' Proposed.
g Chandler Lake, 1995.
36
Table 5. Mean nutrients and phytoplankton biomass (as total chlorophyll) in lakes of Gates
of the Arctic National Park and Preserve.
1992
1993
TN
TP
chl
TN/TP
TN
TP
chl
TN/TP
Lake
(mg/L)
(Mg/U
(Mg/U
(mg/L)
(Mg/U
(Mg/L)
Agiak
a
0.16
7
1.5
23
Amiloyak
0.19
11
1.7
17
0.28
8
1.6
35
Chandler
0.22
6
1.3
37
0.16
5
1.1
32
Itkillik
—
—
—
—
0.29
8
1.0
36
Kipmik
0.19
6
1.8
32
0.19
6
3.4
32
Kurupa
Matcharak
0.41
8
1.0
51
0.41
12
2.9
34
Minakokosa
0.47
6
1.7
78
—
—
—
—
Narvak
0.40
5
1.3
80
0.32
4
1.5
80
Nutuvukti
0.30
5
1.5
60
0.27
5
1.6
54
Pingo
0.76
16
2.1
48
—
—
—
—
Selby
—
—
—
—
0.30
4
1.3
75
Summit
—
—
—
—
0.18
6
1.1
30
Takahula
0.35
4
0.7
88
0.21
4
1.2
52
Tulilik
Walker
0.32
4
0.8
80
0.34
5
0.7
68
1995
Lake
TN TP chl TN/TP
(mg/L) (ug/L) (ug/L)
Agiak
0.11
9
1.9
12
Amiloyak
—
—
—
—
Chandler
0.11
8
1.4
14
Itkillik
0.25
7
1.2
36
Kipmik
0.11
5
1.4
22
Kurupa
0.13
11
0.5
12
Matcharak
0.32
9
2.9
36
Minakokosa
—
—
—
—
Narvak
—
—
—
—
Nutuvukti
—
—
—
—
Pingo
—
—
—
—
Selby
—
—
—
—
Summit
0.12
21
2.6
6
Takahula
0.15
3
1.3
50
Tulilik
0.44
7
1.4
63
Walker
0.26
3
1.3
87
a Dash means not measured.
37
Table 6. Multi-year average nutrients and phytoplankton biomass (as total chlorophyll) in
lakes of Gates of the Arctic National Park and Preserve.
TN
TP
chl
TNATP
Lake
(mg/L)
(Mg/D
(Mg/U
Agiaka
0.133
8
1.7
17
Amiloyak3
0.235
10
1.6
24
Chandler*3
0.162
6
1.3
27
Itkillik3
0.280
8
1.1
35
Kipmikb
0.162
6
2.2
27
Kurupac
0.127
11
0.5
12
Matcharakb
0.380
10
2.3
38
Minakokosac
0.471
6
1.7
78
Narvaka
0.360
4
1.5
90
Nutuvuktia
0.285
5
1.6
57
Pingoc
0.760
16
2.1
48
Selbyc
0.300
4
1.3
75
Summit3
0.150
14
1.8
11
Takahula^
0.238
4
1.1
60
Tulilikc
0.435
7
1.4
62
Walked
0.309
4
0.9
77
a Two years.
" Three years.
c One year.
38
Table 7. Results of nutrient stimulation bioassay experiments in lakes of Gates of the Arctic
National Park and Preserve, expressed as ratio of final to initial total chlorophyll.
(C = control, +P = additional phosphorus added, +N = additional nitrogen added,
and +N&P = additional nitrogen and phosphorus added). Walker Lake results for
1 988 are found in Jones et al. (1 990).
Duncan's Test
Lake and Year
C
+P
+N
+N&P
Result
Agiak, 1 995
1.12
1.11
2.52
6.30
NP>N>C=P
Agiak, 1995
1.16
1.08
2.73
5.88
NP>N>C=P
Chandler, 1995
1.40
1.80
1.33
2.27
NP>P>C=N
Itkillik, 1995
0.82
0.88
1.76
5.94
NP>N>P=C
Itkillik-South, 1989
0.79
0.80
2.42
5.33
NP=N=P=C
Itki Nik-North, 1989
1.28
1.14
2.64
6.68
NP>N>C=P
Kipmik, 1995
0.60
0.72
1.73
5.46
NP>N>P=C
Kipmik, 1995
0.50
0.56
1.10
3.64
NP>N=P=C
Matcharak, 1 995
0.79
0.80
2.42
5.33
NP>N>P=C
Narvak-North, 1 993
0.85
1.93
1.09
2.24
NP>P>N>C
Narvak-South, 1 993
0.70
1.26
0.79
1.66
NP>P>N=C
Selby-North, 1993
1.42
2.63
1.46
3.52
NP>P>N=C
Sel by-East, 1993
0.78
1.18
0.82
1.43
NP=P=N=C
Summit Lake, 1995
1.07
1.33
1.66
2.79
NP>N=P=C
Summit Lake, 1995
0.97
1.11
1.25
2.44
NP>N>P=C
39
Table 8. Discrete total chlorophyll values for specific depths, lakes of Gates of the Arctic
National Park and Preserve.
Lake
Depth (m)
chl (ug/L)
Lake
Depth (m)
chl (ug/L)
1992
Chandler
1
1.2
Kipmik
1
1.2
4.5
1.2
6
3.6
9
1.2
12
1.6
12
1.3
Matcharak
1
0.5
Minakokosa
1
0.7
5
0.7
6
3.2
8
1.2
10
2.6
Narvak
1
1.2
Nutuvkti
1
1.4
5
1.5
6
1.8
7.5
1.7
10
1.8
15
0.5
12
0.8
Takahula
1
0.3
Walker
1
0.6
6
0.9
5
0.8
12.5
1.1
12.5
0.8
25
0.4
25
0.6
1993
Narvak
0
1.0
Narvak
0
1.0
(south end)
2
1.3
(mid-lake)
2
0.9
4
1.8
4
0.9
6
1.8
5
1.2
7
2.0
6
2.2
8
2.2
7
1.9
9
1.9
8
1.9
10
0.7
10
2.4
12
1.0
12
1.4
14
0.6
14
0.9
16
0.5
16
0.7
Selby
0
0.9
Takahula
1
0.3
2
0.8
15
1.7
4
0.8
30
0.8
6
1.0
7
1.2
8
1.8
10
1.9
12
2.0
14
1.4
1995
Takahula
1
0.34
Walker
1
0.24
5
0.47
15.6
1.46
16.4
1.24
31.2
1.90
32.8
1.05
40
Table 9. Light levels at depths of total chlorophyll peaks, lakes of Gates of the Arctic
National Park and Preserve.
Light Level at
Lake Peak Depth (m) Peak Depth (%)
1993
Narvak (south) 8 3
Narvak (mid-lake) 10 1
Selby 1 0 2
12 1
Takahula 15 3
1^95
Takahula 16.4 1
Walker 15.6 4
41
Table 1 0. Light conditions (means), lakes of Gates of the Arctic National Park and
Preserve. [Kj (PAR) is the extinction coefficient of photosynthetically active
radiation].
Secchi
1 % Light
Apparent
Kd (PAR)
Depth
Depth
Color
Turbidity
Phytoplankton
Lake
(m-1)
(m)
(m)
(Pt-Co Units)
(NTU)
(mgm~3chl)
Agiaka
0.464
4.8
10.3
25
1.1
1.7
Amiloyak3
0.262
4.6
17.6
19
1.1
1.6
Chandlerb
0.520
3.6
9.80
25
3.2
1.3
Itkillik3
0.290
9.2
16.0
12
0.42
1.1
Kipmikb
0.420
7.0
11.1
12
0.52
2.2
Kurupac
1.53
0.6
3.01
83
18.
0.5
Matcharakb
0.330
7.8
14.0
9.4
0.56
2.3
Minakokosac
—
5.8
—
14
—
1.7
Narvak3
0.433
8.7
10.4
12
0.36
1.5
Nutuvukti3
0.433
6.4
10.4
16
0.43
1.6
Pingoc
—
—
—
20
—
2.1
Selbyc
0.404
8.6
11.4
17
0.35
1.3
Summit3
0.962
3.8
7.5
56
7.5
1.8
Takahulab
0.255
14.6
18.2
5.0
0.32
1.1
Tulilikc
0.420
7.3
11.0
8.0
0.44
1.4
Walkerb
0.252
14.1
18.7
4.3
0.27
0.9
3 Two years.
b Three years.
c One year.
42
Table 1 1 . Composite light characteristics, lakes of Gates of the Arctic National Park and
Preserve. (1 % = 1 % light depth (m), SD = Secchi depth (m), and % PAR at SD
% photosynthetically active radiation at the Secchi depth).
Lake 1 %:SD % PAR at SD
Agiak 2.1 11
Amiloyak 3.8 30
Chandler 2.7 15
Itkillik 1.7 7
Kipmik 1.6 5
Kurupa 5.0 40
Matcharak 1 .8 8
Minakokosa — —
Narvak 1 .2 2
Nutuvukti 1.6 6
Pingo — —
Selby 1.3 3
Summit 2.0 3
Takahula 1.2 2
Tulilik 1.5 5
Walker 1.3 3
43
Table 1 2. Average concentration of zooplankton as dry weight and as organic material
(ash-free dry weight) for lakes of Gates of the Arctic National Park and Preserve.
1992
1993
Haul
Dry
Ash -free
Haul
Dry
Ash-Free
Depth
Weight
Dry Weight
Depth
Weight
Dry Weight
Lake
(m)
(mg/m3)
(mg/m3)
(m)
(mg/m3)
(mg/m3)
Agiak
a
12
33.8
30.6
Amiloyak
3
75.8
37.1
7
80.0
62.3
Chandler
12
12.5
8.3
12
34.0
22.0
Itkillik
—
—
—
10
106.
99.2
Kipmik
13
15.8
14.2
25
6.7
5.8
Kurupa
—
—
—
—
—
—
Matcharak
9.5
33.7
22.6
17
74.7
70.6
Minakokosa
45
17.4
10.4
—
—
—
Narvak
35
6.6
6.5
8
27.1
24.5
Nutuvukti
30
25.1
20.1
15
13.6
11.4
Pingo
—
—
—
—
—
—
Selby
—
—
—
15
9.4
8.0
Summit
—
—
—
10
26.3
23.7
Takahula
20
48.5
40.1
45
15.3
14.3
Tulilik
—
—
—
—
—
—
Walker
69
6.9
5.1
50
7.1
6.2
1995
Haul
Dry
Ash -free
Depth
Weight
Dry Weight
Lake
(m)
(mg/m3)
(mg/m3)
Agiak
12
31.7
21.4
Amiloyak
—
—
—
Chandler
12
6.0
2.7
Itkillik
8
164
146
Kipmik
22
18.5
14.7
Kurupa
21
7.8
5.5
Matcharak
14
69.2
61.7
Minakokosa
—
—
—
Narvak
—
—
—
Nutuvukti
—
—
—
Pingo
—
—
—
Selby
—
—
—
Summit
9
13.7
10.2
Takahula
41
20.4
16.8
Tulilik
7
179
167
Walker
70
15.0
11.1
Dash means not sampled.
44
Table 13. Counts of zooplankton (#/m3), 1993 samples, lakes of Gates of the Arctic
National Park and Preserve.
Lake
Copepods
Cladocera
Ceratium
Rotifers
Ci Mates
Agiak
3628
6
6
73
0
Amiloyak
3105
56
0
431
299
Chandler
288
6
0
0
0
Itkillik
7407
331
7852
571
0
Kipmik
344
45
9
691
0
Matcharak
1764
125
16
455
0
Narvak
1452
375
389
662
0
Nutuvukti
608
8
0
0
0
Selby
524
148
538
1369
48
Summit
1560
74
0
118
14
Takahula
907
23
57
719
0
Walker
331
34
53
52
0
45
Table 14. Counts of copepods (#/m3), 1 993 zooplankton samples, lakes of Gates of the
Arctic National Park and Preserve.
Lake
Calanoid
Harpactacoid
Cyclopoid
Nauplii
Copepodites
Agiak
134
19
0
3470
4
Amiloyak
602
0
201
2283
20
Chandler
248
8
0
0
33
Itkillik
507
92
2
6442
364
Kipmik
57
3
0
64
221
Matcharak
482
38
0
1068
531
Narvak
110
17
0
741
585
Nutuvukti
112
26
0
3
464
Selby
54
6
2
207
94
Summit
212
44
0
772
532
Takahula
133
18
0
324
432
Walker
47
5
0
190
94
46
Table 1 5. Productivity indicator ranking — high to low — of lakes of Gates of the Arctic
National Park and Preserve.
Morphoedaphic
Alkalinity
Index
Average
(meq/L as
(mg/L total
Lake
Depth (m)
Lake
CaC03)
Lake
ions/z)
Pingoa
0.62
Pingo
3.098
Pingo
370.
Tulilik3
3.8
Takahula
2.552
Itkillik
25.
Amiloyak
3.9
Itkillik
2.024
Tulilik
21.
Summit3
4.2
Matcharak
1.964
Matcharak
18.
Agiak
5.2
Walker
1.101
Amiloyak
7.6
Itkillik
5.8
Tulilik
1.083
Kurupa
6.9
Kipmik
8.6
Kurupa
0.941
Takahula
6.4
Matcharak
12.
Narvak
0.512
Chandler
4.1
Chandler
14.
Selby
0.468
Summit
4.0
Selby
15.
Chandler
0.432
Selby
4.0
Kurupa
15.
Nutuvukti
0.430
Agiak
2.0
Nutuvukti
20.
Minakokosa
0.320
Nutuvukti
1.8
Takahula
32.
Amiloyak
0.284
Kipmik
1.5
Minakokosa
36.
Summit
0.168
Walker
1.4
Walker
61.
Kipmik
0.158
Minakokosa
1.0
Narvak
62.
Agiak
0.112
Narvak
1.0
Mean depth estimated as anchor depth divided by 2.4.
47
Table 1 6. Stream conditions, John River and tributaries at Anaktuvuk Pass.
1993
1994
Flow (m3/sec)
Flow (m3/sec)
Little Contact Creek
0.39
0.27
Big<
Contact Creek
1.0
2.6
John
i River
-6.8
a
1993
pH
Cond.
(uS/cm)
Temp.
(°C)
D.O.
(mg/L)
Turbidity
(NTU)
323
0.1
11.9
0.18
252
0
—
0.25
240
3.7
11.0
0.34
Little Contact Creek — "
Big Contact Creek —
John River 7.21
1994
pH
Cond.
(uS/cm)
Temp.
(°C)
D.O.
(mg/L)
Turbidity
(NTU)
Color
(cpu)
Little Contact Creek
7.40
286
7.8
—
1.0
5
Big Contact Creek
7.52
168
7.5
—
1.0
8
John River
—
213
7.1
—
2.0
7
a Too deep for method.
° Dash indicates not measured.
48
Table 1 7. Ion balances, John River and tributaries at Anaktuvuk Pass.
Little Contact Cr.
(mg/L) (meq/L)
Big Contact Cr.
John R.
(mg/L)
(meq/L)
(mg/L)
(meq/L)
Cu
49.3
2.465
31.8
1.587
36.3
1.811
Mg
8.59
0.707
5.06
0.416
5.60
0.461
Na
0.86
0.037
0.51
0.022
0.54
0.023
K
<0.5
<0.013
<0.5
<0.013
<0.5
<0.013
Cations
3.209
2.025
2.295
HC03
112.5
1.84
69.6
1.140
87.3
1.431
SO4
70
1.458
48.0
0.999
49.3
1.026
CI
3.1
0.087
2.6
0.073
3.2
0.091
Anions
3.385
2.212
2.548
Total Ions
6.591
4.237
4.843
49
Table 1 8. Trace metal characteristics (ICP) of the upper John River (Big Contact Creek,
Little Contact Creek, and the John River at Anaktuvuk) samples, September
1 993. A dash means criterion (USEPA) is not yet set.
Laboratory
Detection
Acute
Chronic
Limit
Criterion
Criterion
Criterion
Metal
(mg/L)
(mg/L)
(mg/L)
Detected
Exceedances
Silver (Ag)
0.01
4.1
0.12
Aluminum (Al)
0.02
0.75a
0.087a
Arsenic (As)
0.04
0. 360b
0.190b
Boron (B)
0.02
—
—
Barium (Ba)
0.0034
—
—
Yes
N/A
Beryllium (Be)
0.0005
0.130c
0.0053c
Bismuth (Bi)
0.04
—
—
Cadmium (Cd)
0.002
0.0039d
0.001 1d
Cobalt (Co)
0.01
—
—
Chromium (Cr)
0.01
0.001 6e
0.0011
Copper (Cu)
0.003
0.001 8d
0.001 2d
Iron (Fe)
0.005
—
1.000
Yes
No
Lithium (Li)
0.002
—
—
Manganese (Mn)
0.002
—
—
Molybdenum (Mo)
0.005
—
—
Nickel (Ni)
0.01
1 .400d
0.1 60d
Phosphorus (P)
0.09
—
—
Lead (Pb)
0.04
0.083d
0.0032d
Antimony (Sb)
0.04
0.088f
0.030f
Selenium (Se)
0.04
0.020
0.005
Silicon (Si)
0.005
—
—
Yes
N/A
Tin (Sn)
0.04
—
—
Strontium (Sr)
0.001
—
—
Yes
N/A
Titanium (Ti)
0.002
—
—
Thallium (Tl)
0.08
—
—
Vanadium (V)
0.003
—
—
Zinc (Zn)
0.002
0.112 d
0.103 d
a pH 6.5-9.
b Arsenic (III).
c Lowest Observed Effect Level.
d Hardness dependent criteria (100 mg/L as CaCC>3 used).
e Cr (VI).
' Proposed.
50
Table 1 9. Bacterial analysis, John River and tributaries, late summer 1 993 and 1 994.
# Colonies/100
mL
Membrane
Total
Fecal
Fecal
Site
Sample Date
Coliform Coliform
Coliform
John River
31 Aug 1993
23.0
1.1
<2
16.1
<1.1
<2
16.1
<1.1
<2
Big Contact Creek
1 Sep 1993
5.1
<1.1
<2
6.9
<1.1
<2
3.6
<1.1
2
Little Contact Creek
1 Sep 1 993
3.6
<1.1
<2
2.2
<1.1
<2
5.1
1.1
2
John River
1 6 Aug 1 994
POSa
POS
POS
NDb
ND
ND
Big Contact Creek
16 Aug 1994
POS
POS
POS
ND
POS
ND
Little Contact Creek
16 Aug 1994
POS
POS
POS
ND
POS
ND
a POS = positive.
° ND = none detected.
51
Table 20. Total petroleum hydrocarbons (TPH), John River and tributaries, 1 993 and
1 994. Three replicates per site per date.
Site Sample Date TPH (mg/L)
John River 31 Aug 1993 0.5
<0.4
<0.4
Big Contact Creek 1 Sep 1 993 <0.4
<0.4
<0.4
Little Contact Creek 1 Sep 1 993 <0.4
<0.4
<0.4
John River 16 Aug 1994 0.6
0.7
<0.4
Big Contact Creek 16 Aug 1994 0.6
0.8
0.8
Little Contact Creek 1 6 Aug 1 994 0.9
0.7
0.7
52
Itkilik L
Kc*ukp
100 mi
Figure 1 . Gates of the Arctic National Park and Preserve with study lakes and streams.
53
Agiak Lake
Physical and chemical data
o-
5-
J= 10-
(D
Q
15-1
20-
0 4 8 12 16
1 i i i I ■ ■ i I i i — i I i i i
17 July 1993
T-i — i i i — i — i i i — i — i i i i i i
15-
20-
8 July 1995
-»-
Temp (°C)
— •—
pH
-&-
D.O. (%satx0.1)
-A-
D.O. (mg/L)
— ♦—
Conductivity (|iS/cm )
<0.1)
-©-
ORP(mVxO.OI)
I I I I 1 I 1 I I I I I I I I I
Figure 2. Water quality profiles, Agiak Lake.
54
Amiloyak Lake
Physical and chemical data
0 2 4 6 8 10 12
0
1
2
I3"
■B 4-
Q.
Q B
6-
7-
8
J I L
J L
August 20, 1991
o- ~
2_~.
3-
4_...
5- -
6- -
7-~
8-
Physical and chemical data
0 2 4 6 8 10
I I I I
©"!•♦
OjO
©i>
A Br- -
trmr -
July 14, 1992
10 12
10
0-
1 -
2-
13~
£ 4-
Q.
Q 5~
6-
7-
8-
4
J I l
12
16
July 17, 1993
12
I
16
-■-
Temp(°C)
-•—
PH
~A-
D.O. (%satx0.1)
-A-
D.O. (mg/L)
— ♦—
Conductivity (u.S/cm x 0.1)
-©-
ORP(mVx0.1)
Figure 3. Water quality profiles, Amiloyak Lake.
55
Chandler Lake
Physical and chemical data
0 4 8 12
I i I i i i i i i i I i i i i i i i I i i i i
20-
0-
| 1 1 i i 1 1 1 1 1 i i 1 1 1 1 1 i i 1 1 i 1 1 1 i i i
0 4 8 12
0 4 8 12
1 i t i i i i i 1 1 i i i i i i I i I ■ i ■ ■
20-
Jiily 17, 1993
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 4 8 12
Physical and chemical data
0 4 8 12
I i t i i i i i I i i i i i i i I i i i i i i i I i i i i
10-
15-
20-
July 14, 1992
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 4 8 12
0-
5-
10-
15--
20-
1 1 1 1 i i i i 1 1 1 i i i i i | i i i i i i i | i i i i
0 4 8 12
-■-
Temp (°C)
-•-
PH
-A-
D.O.
(%satx0.1))
-A-
D.O.
(mg/L)
-♦—
Conductivity (u.S/cm x
0.1)
"e-
ORP
(mVxO.01)
Figure 4. Water quality profiles, Chandler Lake.
56
Itkillik Lake
Physical and chemical data Physical and chemical data
o-
2-
q. :
a)
Q 8"
10-
12-
0 5 10 15
1 i ■ i ■ I i ■ ■ ■ I i i i i I ■ ■
/: :
8July 1989
i i i i i i i i i i i i i i i i i i i
o-
2-
4-
6-
8-
10
0 5 10 15
1 i i i i I ■ ■ i ■ I i i i_ i I i i i
t
12j 11. July 1989
i i i i i i i i i i i i i i i i i i i
10H
12
I ■ ■ ,
10 15
i I i i i i I i i i i I i i i
July 16, 1993.
o-
2-j
4 -m
6-_
8~
10-j
12-
■ i i t i ■ i i
10 15
■ i i I i i i i I i i i
July 10, 1995 L
i i i i i i i i i i i i i i i i i i
-»-
Temp (°C)
-•-
pH
-A-
D.O. (%satx0.1)
-A-
D.O. (mg/l)
— ♦—
Conductivity (|iS/cm >
(0.01)
-®-
ORP (mVxO.01)
Figure 5. Water quality profiles, Itkillik Lake.
57
Kipmik Lake
Physical and chemical data Physical and chemical data
o-
40-
0 4 8 12 16
1 ' ■ ■ I ■ ■ ■ I ' ■ ' I ■ ■ ' I ■
j Aug 16, 1991
i i i i i i i i i i i i i i i i i i
8 12 16
0-
10-
20-
30 - -
40-
10-
£20-
Q.
0)
Q
30 H
40-
0 4 8 12 16
1 ■ ■ ■ I ' ' I I ' ' i I i ■ ' ' i
July 19, 1993
i i i i i i i i i i ii i i i i i i
o-
10-
20-
30-
40- -
July 11, 1995
i i i i i i i i i i i i i i i i i
-m-
Temp (°C)
— •-
pH
-&-
D.O. (%satx0.1)
-A-
D.O. (mg/L)
— ♦—
conductivity (jj.S/cm >
(0.01)
-©-
ORP (mVxO.01)
Figure 6. Water quality profiles, Kipmik Lake.
58
Matcharak Lake
Physical and chemical data
0 5 10 15 20
1 ' ■ ■ ■ I ' ' ■ ■ I ' ■ ' ■ I ' ' ■ ■ I
0-
5-
£ IO-
CS.
CD
Q 15-
20-
August 15, 1991
i i 1 1 i 1 1 1 1 1 1 1 i i i 1 1 i i i |
Physical and chemical data
0 5 10 15 20
1 i i i i I i i i i I i i i i I i i i i I
0-fT
5-
10-
15-
■- 20--
i i i i | i i i i | i i i i | i i i i |
0-
^ 5-
■£ 10-
Q 15-
20 - -
0 5 10 15 20
1 i t i i I i i i i I i i i i I i i i ■ '
[July 19, 1993
1 1 1 i 1 1 1 1 1 | i i i 1 1 1 1 i i
0 5 10 15 20
1 ' ' ■ ■ I ■ ■ ■ ' I ' ' ' ' I ■ ■ ■ ■ I
10-
15-
20-
July 11, 1995
i i i i i i i i i i i i i i i i i i i i
-»-
Temp (°C)
^
PH
D.O. (%satx0.1))
-*-
D.O. (mg/L)
— ♦—
conductivity (u.S/cm x 0.01)
-©-
ORP(mVxO.OI)
Figure 7. Water quality profiles, Matcharak Lake.
59
Narvak Lake
Physical and chemical data Physical and chemical data
i i i i i 1 1
21 August 1991-
i i i i i i i r
i ' ' i > i
10 15 20
0-
10-
20-
30-
40-
50-
60-
I .... I .... I
i i i i i i i i i i i i
13 July 1992
i i i i i i i i i i i i i i i i i i i i i
o-
10-
^20-
£ 30-
Q.
S 40-
50-
60-
0 5 10 15 20
1 ' ' ■ ' I ' ' ■ ■ I ■ ' ' ■ I ■ ■ ' ■ '
21 July 1993
i i i i i i i i i i i i i i i i i i i
Temp (°C)
pH
DO(%satx0.1)
DO (mg/L)
Conductivity (u.S/cm x 0.1)
ORP(mVxO.OI)
Figure 8. Water quality profiles, Narvak Lake.
60
Nutuvukti Lake
Physical and chemical data Physical and chemical data
o-
5-
^ 10-
£ 15-
Q.
CD
Q 20H
25-
30-
0 5 10 15
1 i i i i I i i i i I i i i i I i i i
0-
10
20-
! August 21, 1991
i i i i i i i i i i i i i i i i i i i
30-
40
50 - -
0 5 10 15
1 ■ ■ ■ ■ I ■ i ■ ' I i ■ ■ ' I ■ I
<<► (>
* j *July 15, 1
992
i i i i i i i i i i i i i i i i i i i
20 - -
0 5 10 15 20 25
1 i i i i I i ■ t ■ I ■ i i i I i i i i I i i i ■ I
July 20, 1993
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
-m-
Temp (°C)
-#-
pH
-£x-
D.O. (%satx0.1)
-h-
D.O. (mg/L)
— ♦—
Conductivity (uS/cm x 0.01 )
-©-
ORP(mVxO.OI)
Figure 9. Water quality profiles, Nutuvukti Lake.
61
Selby Lake
Physical and chemical data
o- -
5-
S io-
Q.
Q
15 —I
5 10 15 20 25
I ■ ■ ■ ■ I » ■ ■ ■ I ■ ■ ■ ■ I ■ ' ■ ■ I ■ ■ ■ ■ I
August 22, 1991
20— j- [ • j ■ I
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0-
5-
£ 10
Q.
0)
Q
15-
20-
0 5 10 15 20 25
1 i i i i I ■ i i i I i i ■ i I t i i i I t i i i I
July 21, 1993
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Temp (°C)
D.O. (mg/L)
Figure 10. Water quality profiles, Selby Lake.
62
Summit Lake
0-
2-
4-
1 e-i
£ :
Q- 8-
Q
10-
12-
14-
Physicai and chemical data
0 2 4 6 8 10 12 14
1 ■ ■ ■ I ■ ■ ■ I ■ ' ■ I ■ ■ ■ I ■ ' ' I ' ' ' I ■ ' ■ I ■ '
0-
2-
4-
6-
°- 8-
10-
12-
14-
l i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i
0 2 4 6 8 10 12 14
1 i t i I i i i I i i i I i i i I i i i I i i i I i i i I i i
July 10, 1995
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Temp (°C)
pH
D.O. (%satx0.1)
D.O. (mg/L)
Conductivity (^iS/cm x 0.1)
ORP(mVxO.OI)
Figure 1 1 . Water quality profiles, Summit Lake.
63
Takahula Lake
Physical and chemical data Physical and chemical data
5 10 15 20
0-
10-
- E 20-
60-
— £ 30-
- 0 40-
14 August . ^,n
1991
i i i i i i i i i i i i i i i i i i i i i
0 5 10 15 20
50
60-
17 July
1992
i i i i i i i i i i i i i i i i i i i i
0 5 10 15 20
0 5 10 15 20
■ i > I i i ■ ■ I i i i i I ■ i i i I
I i i i i | i i i i | i i i i | i i i i
0 5 10 15 20
60-
5 10 15 20
I i i i i I ■ ■ ■ t I i i i i I i i i , l
7 July
1995 ~
i i i i i | i i i i | i i i i | i i i i |
0 5 10 15 20
Temp (°C)
pH
DO(%satx0.1)
DO (mg/L)
Conductivity (uS/cm x 0.01 )
ORP(mVxO.OI)
Figure 12. Water quality profiles, Takahula Lake.
64
Walker Lake-1 988
Physical and chemical data Physical and chemical data
o-
10-
E 20-
0 30H
Q
40-
50-
0 5 10 15 20
1 ■ ■ ■ ■ I ■ ■ ■ ' I ■ ■ ■ ■ I ■ ■ ■ ■
500m off creek
In West Cove
12 July 1988
o-
10-
20-
30-
40-
i i i i | i i i i | i i i i | i i i i |
0 5 10 15 20
■ i i i I i t ■ ■ I i i i ■ I i i i i '
i- 50-
0-f
10-
E 20-
Q.
CD 30 -|
Q
40
50-
0 5 10 15 20
1 ■ ■ I I ■ ■ ■ ■ I ■ ■ ■ ■ I ■ ' ■ ■ '
Center of West Cove
9 July 1988
i i i i i i i i i i i i i i i i i i i i i
Temp (°C)
Figure 1 3. Water quality profiles, Walker Lake, 1 988.
65
Walker Lake
Physical and chemical data Physical and chemical data
o--
10--
20 - -
30 - 4
CD ^u I
50-
60-
70- -
10
15
20
15 July 1992
10
15
20
0-
10-
20-
>B 30-
°- 40-
50-
60-
70
-»-
Temp (°C)
-♦-
pH
—&-
D.O. (%satx0.1)
-±-
D.O. (rug/L)
— ♦—
Conductivity (nS/cm )
<0.01)
-©-
ORP(mVxO.I)
Figure 14. Water quality profiles, Walker Lake.
66
Physical and chemical data Physical and chemical data
0 5 10 15 20
1 ■ ■ ■ ■ I ■ ■ ■ ■ I ■ ■ ■ ■ I ■ ■ ■ » I
0 5 10 15 20
1 i i i i I i i i i I i i i i I i t i i
July
1992
Minakokosa
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
o.o-
0.5-
r 1.0
1.5
2.0-
«c
o
#
16 July 1992
Pingo
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 5 10 15 20
I ■ ■ ■ ■ I ■ ■ ■ ■ I ■ ■ ■ ■ I
30-
40-
6 July 1995
Kurupa
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
o-
2-
4-
6-
8-
10-
12-
0 5 10 15 20
1 i ■ i i I t i i i i i i i i i i t i i
O
C)
♦ o
()
()
()
()
0
6 July 1995
Tulilik
1 1 1 i 1 1 1 1 1 i i i 1 1 i 1 1 i 1 1 i
Temp (°C)
PH
D.O(%satx0.1)
DO. (mg/L)
Conductivity QjS/cm x 0.01)
ORP(mVxO.OI)
Figure 1 5. Water quality profiles, Minakokosa, Pingo, Kurupa, and Tulilik Lakes.
67
2-
E
O)
10-
9-
8-
7-
6-
5-
4-
3-
2-
1-
9-
8-
7-
6-
5-
Pingo
Tulilik
Kurupa
/
Matcharak
Chandler
Agiak
Takahula
Amiloyak
Walker
Minakokosa
n — i — i i i
5 6 7 8 9
10
t — i — n-
5 6 7 8
Ca (mg/L)
Figure 16. Relation between magnesium and calcium in lakes of Gates of the Arctic
National Park and Preserve.
68
100— f
9-
8-
7-
6-
5-
4-
3-
■
o
CO
CD
CO
LL
2-
10— |
9-
8-
7-
6-
5-
4-
3-
2-
1-
J I I I I
J I ' ' ' ■
Amiloyak
Itkillik
Walker
Chandler
"i — i — i i i i i
4 5 6 7 8 9 '
10
-1 — I I I I
5 6 7 8 9 '
100
MEI
Figure 1 7. Fish density and the morphoedaphic index of four lakes, Gates of the Arctic
National Park and Preserve.
69
Appendix A. Bathymetric maps of study lakes that are mapped, Gates of the
Arctic National Park and Preserve.
70
N
Agiak Lake
R.E. Reanier 1986
Depths in meters
Transect locations
0.5 kilometer
-i 0.5 mile
71
N
Transect locations
Amiloyak Lake
R.E. Reanier 1986
Depths in meters
3 0.5 Kilometer
i 0.5 mile
72
N
Transect locations
handler Lake
E. Reamer 1986
pths in meters
1 kilometer
■ 1 mile
73
N
Transect locations
Itkillik Lake
R.E. Reanier 1987
Depths in meters
1 kilometer
1 mile
74
Transect locations
LAKE
KIPMIK
.5
Km
Depths in meters
CONTOURS OF LAKE DEPTH APPROXIMATED FROM
SINGLE LONGITUDINAL DEPTH PROFILES TAKEN
AT KURUPA & CASCADE LAKES ON 17 AUG. 1979
75
1 k~
fett
76
Transect locations
/
LAKE
MATCHARAK
2. .3 .4 .5
1.0 Km
Depths in meters
77
N
Transect locations
Lake Minakokosa
R.E. Reamer 1986
Depths in meters
3 1 kilometer
s 1 mile
"*0.
•80-
114
«0>
.#,
78
N
Narvak Lake
^
<?<x
R.E. Reanier 1986
Depths in meters
i -i 1 kilometer
i — i 1 mile
79
N
Transect locations
Nutuvukti Lake
R.E. Reanier 1986
Depths in meters
1 kilometer
1 mile
80
N
Lake Selby
R.E. Reanier 1986
Depths in meters
' ' 1 kilometer
' — ' 1 mile
81
Q -I .2 .3 .4 .5 km
1 1 I — l ' I
Depths in meters
Transect locations
/
N
I
TAKAHULA
LAKE
82
50R
N
Transact locations
}r& i
;^7 \|
;\^y
/ A
.///I
I I
flW«i
\1 1
^
^
Walker Lake
R.E. R*ani*r 19SS
Dooths in m«t«f)
Contour interval 10 m«tora
1 kllom*1*r
a 1 mil*
83
Appendix B. Trace and major metals (mg/L) of lakes of Gates of the Arctic
National Park and Preserve— 1 992, 1993, and 1995.
J2
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Appendix C. Nutrients and total chlorophyll concentrations of plankton of lakes
of Gates of the Arctic National Park and Preserve — 1 992, 1 993, and
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(1 %) in m, color in chlorophosphate units (cpu), and turbidity in
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96
Appendix F. Monitoring Plan
by Patty Rost, Nancy Deschu, and Jacqueline D. LaPerriere.
97
LAKE MONITORING PLAN
GATES OF THE ARCTIC NATIONAL PARK AND PRESERVE
Gates of the Arctic National Park and Preserve (GAAR) encompasses approximately 8.4
million acres of public land in Alaska. These lands hold uncounted lakes that are isolated
from the more common effects of habitat fragmentation, exotic species invasion, urban
sprawl, and nearby industrial pollution seen in the other 49 states. The large park and its
relative isolation, however, have not left the lakes in the park immune from environmental
threats. Climate changes, circumpolar pollutant transport, and nearly 257,000 acres of
private lands within the park pose subtle threats that could affect GAAR lakes in the future.
Baseline water quality information in GAAR was collected in 1 6 lakes through research
between 1992 to 1995. Baseline information on GAAR lakes is useful in making sound
park resource management decisions. Long-term monitoring of these lakes will provide
springboards for further scientific research and alert park management to changes in the
resources. Monitoring waters that have not yet degraded can provide the National Park
Service and the scientific community with data relating to pristine arctic waters and alert
park staff to possible changes in water quality.
This monitoring plan will serve to establish a schedule and sampling scheme to
observe changes in lake water quality in future years. This plan will provide park
management a means to become ready to protect the water quality of lakes within GAAR.
The level of monitoring proposed through this plan assumes that current visitor and local
resident activities will remain fairly constant over the next 10 years. It is also assumed that
development will not occur within park boundaries and will occur at a minimal level
adjacent to the park. As new development activities are proposed near or within the park,
individual project-specific monitoring plans will be developed separate from this plan.
MANAGEMENT ISSUES and CONCERNS
Existing or eminent threats to lake water quality within GAAR are minimal at this time.
Issues that could arise to change the water quality are as follows:
Increased Visitation: As visitation increases in GAAR, it is expected there will be
increased floatplane and boat use on some of the lakes in the park, along with increased
camping on the shores of these lakes. Although these activities do not pose major pollution
98
sources, small cumulative effects from fuel leakage, gray water and human waste from
campsites, and riparian vegetation trampling by campers resulting in erosion are of
concern.
Associated Lakes — Chandler, Itkillik, Summit, Matcharak, Takahula, Walker, Pingo, and
Tulilik
Private Land Development: Development on private land and the potential increase of
established commercial operations within GAAR raises concerns regarding changes in
water quality, particularly on small lakes. Land clearing, sanitation systems, fuel transport
and storage, domestic wastewater discharge, and development of access roads or trails,
and non-point runoff from disturbed areas could cause localized changes in water quality.
Associated Lakes — Chandler, Agiak, Amiloyak, and Walker
Road/Trail Development and Increased Road Use: A road is proposed that would cut
across the southwest area of GAAR along the upper Kobuk River to access mining districts.
This road would open areas of the park that have to date been only accessible by
floatplane. This new access may generate increased awareness of Selby, Narvak,
Nutuvukti, and Walker lakes in the upper Kobuk drainage. Increased public use of the
TransAlaska Pipeline Haul Road along the east side of the park would bring about a greater
awareness of the Itkillik Lake area, and perhaps increased floatplane and hiking access to
the lake, which is only 20 miles from the road.
Associated Lakes — Walker, Nutuvukti, Selby, Narvak, and Itkillik
Oil and Gas Development: There are existing oil and gas tracts in the Itkillik Lake area
as well as on the northern boundary of the park. Itkillik Lake and surrounding tributaries
and wetlands water quality could be affected by runoff from an operation in the area. Road
construction to and around an oil drilling operation would also be a potential source of
pollutants.
Associated Lakes — Killik, Chandler, Amiloyak, Itkillik and Kurupa
Climate Change: Changes in climate over time could affect arctic lakes in several ways:
change in the amount of annual precipitation; the ratio of precipitation falling as rain and
snow; change in snow pack depth; change in timing of spring melt-off; change in melting
rate of permanent snowfields. These changes in hydrologic conditions could affect lake-
water quality through increased scavenging of airborne particulate, dilution of the lake
99
water, and increased watershed input (such as nutrients and sediment) from increased run-
off. This information is important to understanding how a pristine ecosystem changes over
time.
Associated Lakes — Any with current baseline data
Circumpolar Pollution: There is concern in arctic Alaska for the effects of circumpolar
pollution and airborne deposition on water quality. Metals generated by smelting,
pesticide application, refining, and auto exhaust (such as arsenic, lead, and mercury) are
potential pollutants. In addition, precipitation may carry industrial-produced acidity, as
reflected in sulfate measurements. This information is important to understanding possible
effects related to human consumptive use of aquatic resources.
Associated Lakes — Chandler, Kurupa, Itkillik, and Walker
MONITORING PROTOCOL and SCHEDULE
Currently, development in and around the park consists of activities within the Alyeska
Pipeline corridor along the Dalton Highway; growth within the community of the
Anaktuvuk Pass; and development of access routes to private inholding activities. The
following schedule and sampling protocol will allow for each lake surveyed through the
initial synoptic survey to be revisited every 3 years. It also allows for a repeat of the full
synoptic survey described this report (LaPerriere 1 999) every 5-1 0 years. Duplication of the
synoptic survey will be dependent on the level of funding available from park base
operating funds or the ability to receive special project funding.
This lake monitoring plan acknowledges that the park will not have a water quality
technical specialist on staff. Annual monitoring efforts are planned to be accomplishable
by a general science technician employed by the park. The major duplication of the
synoptic survey will require contracting or hiring a technical expert to collect and analysis
the data.
Annual Cycle
The initial synoptic survey, conducted between 1992 and 1995, focused on 15 lakes split
between the north side and the south side of the Brooks Range in the park. The monitoring
plan will allow for 5 lakes to be monitored annually making it possible to cover all of the
initial baseline lakes over a 3-year period. The following table shows a proposed schedule
100
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101
for ensuring coverage of all the original 15 synoptic lakes with representative north/south
lakes annually. Walker and Itkillik lakes should be monitored annually to provide year-to-
year comparison of north and south lakes.
Monitoring should occur twice during the ice-free season. Allow sufficient time after
spring breakup before initiating data collection to allow for settling of sediments washed in
with snowmelt. Mid-July through mid-September appears to be the optimum sampling
period to develop a representative summertime database. Sampling should occur at one
site in the middle of each lake. The park's YSI meter should be used to collect temperature,
pH, conductivity, and dissolved oxygen at meter depths of 1 , 2, 3, 4, 5, 1 0, 1 5, 20, 25, 35,
45, 55, etc., down to the bottom (or as far as cable will allow). Integrated water samples
should be collected for turbidity and color measurements. Three separate samples should
be collected at twice the Secchi depth for turbidity and color analysis using Tygon tubing.
The following parameters should be collected annually:
• Secchi disk - use 50-cm size observed through a viewing scope at water surface to
compensate for reflecting light at the surface. Cable should be non-stretching
material such as wire cable or polypropylene cord and be calibrated and marked at
0.25-meter intervals. Record depth at which Secchi disk visibility disappears.
• Color - utilize a Hach portable spectrophotometer. Three integrated water samples
should be collected at each lake for analysis. Take color measurements down to
twice the Secchi depth.
• Turbidity - use a Hach turbidity meter to analyze water samples. Three integrated
water samples should be collected to twice the Secchi depth.
• Conductivity - utilize the YSI meter to take conductivity readings from top to
bottom following the intervals mentioned above.
• Temperature - utilize the YSI meter to take readings from top to bottom following
the intervals mentioned above.
• Chlorophyll - collect three integrated water samples down to twice the Secchi
depth.
• MEI - calculate MEI from conductivity data for each lake.
Five- to 1 0-Year Cycle
Every 5-10 years, a full synoptic survey should be repeated for those lakes that were
sampled between 1992 and 1995. Protocols established during LaPerriere's initial synoptic
study should be followed to allow for data comparison between years. This level of
monitoring cannot be accomplished with general biological expertise. To accurately
102
collect this advanced level of information the park will need to contract or hire a water
quality expert. Parameters include:
Temperature Chloride Secchi depth
pH Total Chlorophyll Light penetration (photometer)
Dissolved Oxygen Total Phosphorous Turbidity
Conductivity Total Nitrogen Alkalinity
Sulfate Trace Metals (including major positive ions)
MEI (calculated) Zooplankton (taxonomy/standing crop)
Color
DATABASE DESIGN
Data should be input into a Geographic Information System (GIS) interface. The NPS
standard is currently Access 2.0. The database should be established prior to field data
collection efforts. Field data form should be developed around the database to allow for
ease of data entry after field collection. A database should be established that has the
following fields:
♦ GPS location of sampling site, site number
♦ Date, time, lake name
♦ Weather at time of sampling
• Cloud cover
• Wind speed/direction
• Precipitation
• Air temperature
• Surface (lake) disturbance level due to wind
♦ Depth of sample
♦ Water temperature
♦ Other specific on-site water chemistry results
♦ Lab results
♦ Environmental changes (i.e. natural landslides, fire, permafrost thaw, etc.)
♦ Name of person collecting sample
♦ Mode of transportation, pilot name/aircraft
Data entry will occur annually after completion of the sampling period.
103
REPORTING
An annual report should consist of a brief narrative that focuses on the lake sampled,
summarizes results of monitoring, and describes level of effort associated with the project.
Information relating to methods and equipment utilized in the project should be
documented as well. A copy of the raw data will be attached. In years when full parameter
monitoring occurs a report should describe the project and the results and provide a
discussion of noticeable water quality differences over time. The report should be written
in a standard scientific format and be peer reviewed by at least three technical experts. It
will then be finalized and distributed to appropriate institutions and park staff.
DEVELOPMENT DRIVEN MONITORING
Monitoring development activities will be crucial in protecting the park's water resources.
Specialized monitoring plans will be developed specifically for each activity as park
management learns of proposed development. Development activities that have the
potential for threatening water quality will be monitored prior to the start of development
and periodically throughout the activity. All threatened waters should have a thorough
collection of baseline data prior to the start of the development activity. Focused baseline
and long-term monitoring will be initiated in association with world-wide catastrophic
pollution events or periods of major climatic change. Even though park management will
not be able to effect the impacts to park resources, information gained will be important to
understanding these global change effects. Baseline data inventory should follow protocols
established by LaPerriere (1999). Suggested parameters to focus monitoring efforts during
these specific time periods, for a variety of issues, are as follows:
Increased Visitation
Potential Impacts: Road/trail development
Human waste
Fuel storage/transport
Land clearing
Parameters: Sedimentation (TSS)
Turbidity (aerial monitoring for plumes in lakes)
Hydrocarbons (motorized equipment use)
Fecal Coliform bacteria (septic systems)
Secchi depth (nutrient color or sediment increase)
104
Road Development
Potential Impacts: Erosion
Stream crossings
Dust
Parameters: Sedimentation (TSS)
Turbidity (aerial monitoring for plumes in lakes)
Hydrocarbons (motorized equipment use)
Oil and Gas Development and Mining
Potential Impacts: Water quantity
Erosion
Hydrocarbon contamination
De-watering
Parameters: Sedimentation (TSS)
Turbidity (aerial monitoring for plumes in lakes)
Hydrocarbons (motorized equipment use)
Metals (drilling muds)
pH
Climate Change
Potential Impacts: Temperature increase or decrease
Runoff increase/decrease
Parameters: Water temperature (at various depths)
Air temperature
Climate data
Circumpolar Pollution
Potential Impacts: Metal concentrations above existing background
Parameters: Metals (deposition from air transport in sediments)
Acid neutralizing capacity
Fire
Potential Impacts: Sedimentation from loss of ground cover
105
Siltation in water from erosion
Chemicals used in fire fighting
Parameters: Sedimentation (TSS)
Turbidity (aerial monitoring for plumes)
Total Nitrogen and Total Phosphorous
HISTORIC BASELINE DATA— WATER QUALITY
The following information is a summary of the lake and stream water quality studies that
have been conducted in GAAR from 1981 to present.
Synoptic survey of 1 6 lakes within GAAR between 1 992-1 995. Specific years for synoptic
survey baseline data collection from LaPerriere (1999) are shown in the following table.
LAKE
INITIAL BASELINE
Itkillik
1993, 1995
Summit
1993, 1995
Chandler
1992, 1993, 1995
Agiak
1993, 1995
Amiloyak
1992, 1993
Tulilik
1995
Kurupa
1995
Takahula
1992, 1993, 1995
Walker
1992, 1993, 1995
Nutuvukti
1992, 1993
Selby
1993
Narvak
1992, 1993
Pingo
1992
Matcharak
1992, 1993, 1995
Kipmik
1992, 1993, 1995
Minakokosa
1995
107
The following parameters were recorded for all lakes surveyed: surface area, latitude,
watershed area, altitude, and landscape characteristics (vegetation and geology).
Volume, mean depth, and maximum depth were calculated for all lakes, except Tulilik,
Pingo, and Summit. These three lakes did not have bathymetric maps completed and the
calculation were not possible.
The following water quality parameters were measured during the lake synoptic survey.
However, not all parameters were measured at all lakes surveyed.
Temperature Trace metals
pH Zooplankton
Dissolved Oxygen Color
Conductivity Total Chlorophyll
ORP Total Phosphorous
MEI Total Nitrogen
Chloride
Seech i depth
Light penetration
Turbidity
Alkalinity
Sulfate
Bathymetry: Lakes surveyed during the synoptic survey have bathymetric maps except
Pingo, Summit, and Tulilik.
Periphyton samples— Selby 1993: included chlorophyll, taxonomy and standing crop.
Nutrient Stimulation experiments
- Selby and Narvak - 1 993
- Chandler, Agiak, Itllkillik, and Kipmik, Matcharak, and Summit - 1 995
-Walker Lake -1998
-Itkillik Lake -1989
National Park Service staff collected water quality data in 1991 on Kipmik, Matcharak,
Nutuvukti, Selby, Narvak, Takahula, Florence Creek, Chandler, and Amiloyak lakes. The
following parameters were measured: pH, dissolved oxygen, temperature, secchi depth,
alkalinity, and hardness.
108
WATER QUALITY BASELINE INVENTORY
Lake and Stream Selection
Following are parameters considered the most important in stratifying the lakes in GAAR in
the future for selecting of addition inventory. GIS will be used to assist in identification and
selection of lakes from the hundreds that are in the park.
1 . Landscape/Vegetation class type (GIS)
2. Geologic underlay (GIS)
3. Watershed size/Lake surface area (GIS)
4. Fish importance/suspected fish importance (NPS records, ADFG surveys and survey
charter operators, local fishing guides)
5. Location in drainage (headwaters, midcourse, etc.)
Other parameters to consider in lake selection for future inventory:
Location - north or south of continental divide
Orientation - for wind effects
Elevation
Surface area
Volume (if bathymetry is known)
Depth (if known)
Trophic state (if known)
N or P limited (if known)
Clarity/light penetration (as of 1999)
MEI if can be calculated
Snow data for existing synoptic lakes or new inventory lakes would be useful in
evaluating pollution effects on water quality. At a minimum, snow data should be
collected from a lake on both the north and south side of the park. The lakes chosen for
snow data collection should be similar in associated watershed size and maximum depth.
Snow sample collection could be arranged in cooperation with the Natural Resource
Conservation Service to benefit both agencies.
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